Look ahead of links/alter links
First Claim
Patent Images
1. A computationally-implemented method comprising:
- obtaining at least a portion of data from a data source;
determining a content of the data;
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system; and
displaying at least one data display option based on the determining an acceptability of a content of the data.
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Accused Products
Abstract
A computationally-implemented method comprises obtaining at least a portion of data from a data source, determining a content of the data, determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system, and displaying at least one data display option based on the determining an acceptability of a content of the data.
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Citations
137 Claims
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1. A computationally-implemented method comprising:
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obtaining at least a portion of data from a data source; determining a content of the data; determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system; and displaying at least one data display option based on the determining an acceptability of a content of the data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68)
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2. The computationally-implemented method of claim 1, wherein the determining a content of the data comprises:
examining a database of known content for data content information.
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3. The computationally-implemented method of claim 1, wherein the determining a content of the data comprises:
traversing at least a portion of the data in real time.
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4. The computationally-implemented method of claim 1, wherein the determining a content of the data comprises:
locally examining at least a portion of the data.
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5. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two viral machine representations operating at least in part on an individual core of a multi-core system comprises:
examining at least a portion of the data to locate references to additional content.
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6. The computationally-implemented method of claim 5, wherein the examining at least a portion of the data to locate references to additional content comprises:
determining whether the data references additional data content information when loading.
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7. The computationally-implemented method of claim 5, wherein the examining at least a portion of the data to locate references to additional content comprises:
issuing a request to a remote computer for additional data content information.
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8. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system at least partially resident within a real machine.
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9. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system at least partially non-resident within a real machine.
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10. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of content of a real machine.
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11. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of software of a real machine.
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12. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two viral machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of hardware of a real machine.
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13. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of an operating system of a real machine.
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14. The computationally implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least a portion of a computing device.
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15. The computationally implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device.
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16. The computationally implemented method of claim 15, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device comprises:
determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device that is at least one of a printer, a fax machine, a peripheral memory device, a network adapter, a music player, a cellular telephone, a data acquisition device, or a device actuator.
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17. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining a state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system prior to loading at least a portion of the data.
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18. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining a state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system subsequent to loading at least a portion of the data.
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19. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining a state change of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system between a prior state and a subsequent state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a system comprising at least two cores after loading at least a portion of the data.
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20. The computationally-implemented method of claim 19, wherein the determining a state change of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system between a prior state and a subsequent state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a system comprising at least two cores after loading at least a portion of the data comprises:
determining whether a state change on at least one of the at least two viral machine representations operating at least in part on an individual core of a multi-core system is an undesirable state change based on one or more end-user specified preferences.
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21. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data in response to at least one user setting.
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22. The computationally-implemented method of claim 21, wherein the determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
determining an acceptability of an effect of content of the data in response to a personal user setting.
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23. The computationally-implemented method of claim 21, wherein the determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
determining an acceptability of an effect of content of the data in response to a peer user setting.
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24. The computationally-implemented method of claim 21, wherein the determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
determining an acceptability of an effect of content of the data in response to a corporate user setting.
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25. The computationally-implemented method of claim 21, wherein the determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
determining an acceptability of an effect of content of the data in response to a work safety user setting.
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26. The computationally-implemented method of claim 21, wherein the determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
determining an acceptability of an effect of content of the data in response to a desirability setting.
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27. The computationally-implemented method of claim 26, wherein the determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
determining an acceptability of an effect of content of the data in response to a religious desirability setting.
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28. The computationally-implemented method of claim 26, wherein the determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
determining an acceptability of an effect of content of the data in response to a political desirability setting.
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29. The computationally-implemented method of claim 26, wherein the determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
determining an acceptability of an effect of content of the data in response to a cultural desirability setting.
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30. The computationally-implemented method of claim 26, wherein the determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
determining an acceptability of an effect of content of the data in response to a theme related desirability setting.
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31. The computationally-implemented method of claim 26, wherein the determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
determining an acceptability of an effect of content of the data in response to an age appropriateness desirability setting.
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32. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data in response to at least one privacy related setting.
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33. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to a user specific privacy related setting.
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34. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to a group privacy related setting.
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35. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to a corporate privacy related setting.
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36. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to transmitted user information.
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37. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to captured user information.
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38. The computationally-implemented method of claim 32, wherein the determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
determining an acceptability of an effect of content of the data in response to exposed user information.
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39. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data in response to visually examining at least a portion of a data image on at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system.
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40. The computationally-implemented method of claim 1, wherein the determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
determining an acceptability of an effect of content of the data at least in part via at least three virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least three virtual machine representations operating at least in part on an individual core of a multi-core system comprising at least three cores.
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41. The computationally-implemented method of claim 1, wherein the displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
providing a data display option of displaying at least a portion of the data.
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42. The computationally-implemented method of claim 1, wherein the displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
providing a data display option of not displaying at least a portion of the data.
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43. The computationally-implemented method of claim 1, wherein the displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
providing a data display option of displaying a modified version of the data.
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44. The computationally-implemented method of claim 43, wherein the providing a data display option of displaying a modified version of the data comprises:
providing a data display option of obfuscating an objectionable data portion.
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45. The computationally-implemented method of claim 43, wherein the providing a data display option of displaying a modified version of the data comprises:
providing a data display option of anonymizing an objectionable data portion.
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46. The computationally-implemented method of claim 43, wherein the providing a data display option of displaying a modified version of the data comprises:
providing a data display option of at least one of removing, altering or replacing an objectionable data portion.
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47. The computationally-implemented method of claim 43, wherein the displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
providing a data display option of displaying a data portion consistent with at least one user-related setting.
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48. The computationally-implemented method of claim 47, wherein the providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
providing a data display option of displaying a data portion consistent with a privacy related user setting.
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49. The computationally-implemented method of claim 47, wherein the providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
providing a data display option of displaying a data portion consistent with a desirability setting.
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50. The computationally-implemented method of claim 47, wherein the providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
providing a data display option of displaying a data portion consistent with a workplace established setting.
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51. The computationally-implemented method of claim 47, wherein the providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
providing a data display option of displaying a data portion consistent with a safety setting.
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52. The computationally-implemented method of claim 51, wherein the providing a data display option of displaying a data portion consistent with a safety setting comprises:
providing a data display option of displaying a data portion consistent with a public safety setting.
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53. The computationally-implemented method of claim 51, wherein the providing a data display option of displaying a data portion consistent with a safety setting comprises:
providing a data display option of displaying a data portion consistent with a home safety setting.
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54. The computationally-implemented method of claim 51, wherein the providing a data display option of displaying a data portion consistent with a safety setting comprises:
providing a data display option of displaying a data portion consistent with a workplace safety setting.
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55. The computationally-implemented method of claim 51, wherein the providing a data display option of displaying a data portion consistent with a safety setting comprises:
providing a data display option of displaying a data portion consistent with a child safety setting.
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56. The computationally-implemented method of claim 1, wherein the displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
redirecting to alternative data.
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57. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
automatically redirecting to alternative data.
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58. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
providing a list of selectable alternative data options.
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59. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a privacy related setting.
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60. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a customized user setting.
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61. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a desirability setting.
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62. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a workplace established setting.
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63. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a user history setting.
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64. The computationally-implemented method of claim 56, wherein the redirecting to alternative data comprises:
displaying alternative data consistent with a safety setting.
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65. The computationally-implemented method of claim 64, wherein the displaying alternative data consistent with a safety setting comprises:
displaying alternative data consistent with a public safety setting.
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66. The computationally-implemented method of claim 64, wherein the displaying alternative data consistent with a safety setting comprises:
displaying alternative data consistent with a home safety setting.
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67. The computationally-implemented method of claim 64, wherein the displaying alternative data consistent with a safety setting comprises:
displaying alternative data consistent with a workplace safety setting.
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68. The computationally-implemented method of claim 64, wherein the displaying alternative data consistent with a safety setting comprises:
displaying alternative data consistent with a child safety setting.
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2. The computationally-implemented method of claim 1, wherein the determining a content of the data comprises:
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69. A computationally-implemented system comprising:
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means for obtaining at least a portion of data from a data source; means for determining a content of the data; means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system; and means for displaying at least one data display option based on the determining an acceptability of a content of the data. - View Dependent Claims (70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136)
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70. The computationally-implemented system of claim 69, wherein the means for determining a content of the data comprises:
means for examining a database of known content for data content information.
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71. The computationally-implemented system of claim 69, wherein the means for determining a content of the data comprises:
means for traversing at least a portion of the data in real time.
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72. The computationally-implemented system of claim 69, wherein the means for determining a content of the data comprises:
means for locally examining at least a portion of the data.
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73. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for examining at least a portion of the data to locate references to additional content.
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74. The computationally-implemented system of claim 73, wherein the means for examining at least a portion of the data to locate references to additional content comprises:
means for determining whether the data references additional data content information when loading.
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75. The computationally-implemented system of claim 73, wherein the means for examining at least a portion of the data to locate references to additional content comprises:
means for issuing a request to a remote computer for additional data content information.
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76. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system at least partially resident within a real machine.
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77. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system at least partially non-resident within a real machine.
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78. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of content of a real machine.
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79. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of software of a real machine.
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80. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of hardware of a real machine.
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81. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a portion of an operating system of a real machine.
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82. The computationally implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least a portion of a computing device.
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83. The computationally implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device.
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84. The computationally implemented system of claim 83, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of a real machine including at least one peripheral device that is at least one of a printer, a fax machine, a peripheral memory device, a network adapter, a music player, a cellular telephone, a data acquisition device, or a device actuator.
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85. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two vial machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining a state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system prior to loading at least a portion of the data.
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86. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining a state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system subsequent to loading at least a portion of the data.
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87. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining a state change of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system between a prior state and a subsequent state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a system comprising at least two cores after loading at least a portion of the data.
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88. The computationally-implemented system of claim 87, wherein the means for determining a state change of at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system between a prior state and a subsequent state of at least one of the at least two virtual machine representations operating at least in part on an individual core of a system comprising at least two cores after loading at least a portion of the data comprises:
means for determining whether a state change on at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system is an undesirable state change based on one or more end-user specified preferences.
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89. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data in response to at least one user setting.
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90. The computationally-implemented system of claim 89, wherein the means for determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
means for determining an acceptability of an effect of content of the data in response to a personal user setting.
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91. The computationally-implemented system of claim 89, wherein the means for determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
means for determining an acceptability of an effect of content of the data in response to a peer user setting.
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92. The computationally-implemented system of claim 89, wherein the means for determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
means for determining an acceptability of an effect of content of the data in response to a corporate user setting.
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93. The computationally-implemented system of claim 89, wherein the means for determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
means for determining an acceptability of an effect of content of the data in response to a work safety user setting.
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94. The computationally-implemented system of claim 89, wherein the means for determining an acceptability of an effect of content of the data in response to at least one user setting comprises:
means for determining an acceptability of an effect of content of the data in response to a desirability setting.
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95. The computationally-implemented system of claim 94, wherein the means for determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
means for determining an acceptability of an effect of content of the data in response to a religious desirability setting.
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96. The computationally-implemented system of claim 94, wherein the means for determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
means for determining an acceptability of an effect of content of the data in response to a political desirability setting.
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97. The computationally-implemented system of claim 94, wherein the means for determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
means for determining an acceptability of an effect of content of the data in response to a cultural desirability setting.
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98. The computationally-implemented system of claim 94, wherein the means for determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
means for determining an acceptability of an effect of content of the data in response to a theme related desirability setting.
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99. The computationally-implemented system of claim 94, wherein the means for determining an acceptability of an effect of content of the data in response to a desirability setting comprises:
means for determining an acceptability of an effect of content of the data in response to an age appropriateness desirability setting.
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100. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting.
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101. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to a user specific privacy related setting.
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102. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to a group privacy related setting.
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103. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to a corporate privacy related setting.
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104. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to transmitted user information.
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105. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to captured user information.
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106. The computationally-implemented system of claim 100, wherein the means for determining an acceptability of an effect of content of the data in response to at least one privacy related setting comprises:
means for determining an acceptability of an effect of content of the data in response to exposed user information.
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107. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data in response to visually examining at least a portion of a data image on at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system.
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108. The computationally-implemented system of claim 69, wherein the means for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system comprises:
means for determining an acceptability of an effect of content of the data at least in part via at least three virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least three virtual machine representations operating at least in part on an individual core of a multi-core system comprising at least three cores.
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109. The computationally-implemented system of claim 69, wherein the means for displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
means for providing a data display option of displaying at least a portion of the data.
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110. The computationally-implemented system of claim 69, wherein the means for displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
means for providing a data display option of not displaying at least a portion of the data.
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111. The computationally-implemented system of claim 69, wherein the means for displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
means for providing a data display option of displaying a modified version of the data.
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112. The computationally-implemented system of claim 111, wherein the means for providing a data display option of displaying a modified version of the data comprises:
means for providing a data display option of obfuscating an objectionable data portion.
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113. The computationally-implemented system of claim 111, wherein the means for providing a data display option of displaying a modified version of the data comprises:
means for providing a data display option of anonymizing an objectionable data portion.
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114. The computationally-implemented system of claim 111, wherein the means for providing a data display-option of displaying a modified version of the data comprises:
means for providing a data display option of at least one of removing, altering or replacing an objectionable data portion.
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115. The computationally-implemented system of claim 111, wherein the means for displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
means for providing a data display option of displaying a data portion consistent with at least one user-related setting.
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116. The computationally-implemented system of claim 115, wherein the means for providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
means for providing a data display option of displaying a data portion consistent with a privacy related user setting.
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117. The computationally-implemented system of claim 115, wherein the means for providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
means for providing a data display option of displaying a data portion consistent with a desirability setting.
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118. The computationally-implemented system of claim 115, wherein the means for providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
means for providing a data display option of displaying a data portion consistent with a workplace established setting.
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119. The computationally-implemented system of claim 115, wherein the means for providing a data display option of displaying a data portion consistent with at least one user-related setting comprises:
means for providing a data display option of displaying a data portion consistent with a safety setting.
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120. The computationally-implemented system of claim 119, wherein the means for providing a data display option of displaying a data portion consistent with a safety setting comprises:
means for providing a data display option of displaying a data portion consistent with a public safety setting.
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121. The computationally-implemented system of claim 119, wherein the means for providing a data display option of displaying a data portion consistent with a safety setting comprises:
means for providing a data display option of displaying a data portion consistent with a home safety setting.
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122. The computationally-implemented system of claim 119, wherein the means for providing a data display option of displaying a data portion consistent with a safety setting comprises:
means for providing a data display option of displaying a data portion consistent with a workplace safety setting.
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123. The computationally-implemented system of claim 119, wherein the means for providing a data display option of displaying a data portion consistent with a safety setting comprises:
means for providing a data display option of displaying a data portion consistent with a child safety setting.
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124. The computationally-implemented system of claim 69, wherein the means for displaying at least one data display option based on the determining an acceptability of a content of the data comprises:
means for redirecting to alternative data.
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125. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for automatically redirecting to alternative data.
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126. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for providing a list of selectable alternative data options.
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127. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a privacy related setting.
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128. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a customized user setting.
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129. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a desirability setting.
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130. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a workplace established setting.
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131. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a user history setting.
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132. The computationally-implemented system of claim 124, wherein the means for redirecting to alternative data comprises:
means for displaying alternative data consistent with a safety setting.
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133. The computationally-implemented system of claim 132, wherein the means for displaying alternative data consistent with a safety setting comprises:
means for displaying alternative data consistent with a public safety setting.
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134. The computationally-implemented system of claim 132, wherein the means for displaying alternative data consistent with a safety setting comprises:
means for displaying alternative data consistent with a home safety setting.
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135. The computationally-implemented system of claim 132, wherein the means for displaying alternative data consistent with a safety setting comprises:
means for displaying alternative data consistent with a workplace safety setting.
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136. The computationally-implemented system of claim 132, wherein the means for displaying alternative data consistent with a safety setting comprises:
means for displaying alternative data consistent with a child safety setting.
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70. The computationally-implemented system of claim 69, wherein the means for determining a content of the data comprises:
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137. A computationally-implemented system comprising:
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circuitry for obtaining at least a portion of data from a data source; circuitry for determining a content of the data; circuitry for determining an acceptability of an effect of content of the data at least in part via at least two virtual machine representations of at least a part of a real machine having at least one end-user specified preference, at least one of the at least two virtual machine representations operating at least in part on an individual core of a multi-core system; and circuitry for displaying at least one data display option based on the determining an acceptability of a content of the data.
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Specification
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Current AssigneeThe Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
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Original AssigneeSearete LLC (Intellectual Ventures LLC)
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InventorsGates, William H. III, Rinaldo, John A. JR., Tegreene, Clarence T., Flake, Gary W., Lord, Robert W., Jung, Edward K.Y., Whitmer, Charles, Levien, Royce A., Wood, Lowell L. JR., Hyde, Roderick A., Malamud, Mark A., Rashid, Richard F.
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Granted Patent
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Time in Patent OfficeDays
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Field of Search
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US Class Current718/1
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CPC Class CodesG06F 16/24575 using contextG06F 21/552 involving long-term monitor...G06F 9/45537 Provision of facilities of ...