Conformed dimensional and context-based data gravity wells
First Claim
1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising:
- receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters;
associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects;
receiving, by the processor, a data stream of non-dimensional data objects;
applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object;
parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object;
parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object;
calculating, by the processor, a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object;
calculating, by the processor, a virtual mass of a parsed conformed dimensional object, wherein the virtual mass of the parsed conformed dimensional object is derived from a formula of;
Pd(C)×
Wtd(S),where Pd(C) is a probability that
1) said one of the non-dimensional data objects has been associated with the correct dimensional label,
2) said one of the non-dimensional data objects is uncorrupted, and
3) said one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; and
where Wtd(S) is the weighting factor of importance of the conformed dimensional object;
creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells;
transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and
defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well.
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Accused Products
Abstract
A processor-implemented method, system, and/or computer program product defines multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of the multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane.
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Citations
20 Claims
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1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising:
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receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving, by the processor, a data stream of non-dimensional data objects; applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; calculating, by the processor, a virtual mass of a parsed conformed dimensional object, wherein the virtual mass of the parsed conformed dimensional object is derived from a formula of;
Pd(C)×
Wtd(S),where Pd(C) is a probability that
1) said one of the non-dimensional data objects has been associated with the correct dimensional label,
2) said one of the non-dimensional data objects is uncorrupted, and
3) said one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; and
where Wtd(S) is the weighting factor of importance of the conformed dimensional object;creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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4. The processor-implemented method of claim 1, wherein the weighting factor of importance of a data object is based on how important the data object is to a particular project.
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5. The processor-implemented method of claim 1, further comprising:
determining that said one of the non-dimensional data objects is uncorrupted by determining that said one of the non-dimensional data objects is not a fragment of an original data object.
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6. The processor-implemented method of claim 1, further comprising:
graphically representing, by the processor, said at least one dimension object and said at least one context object on a wall of said particular context-based conformed dimensional data gravity well.
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7. The processor-implemented method of claim 1, further comprising:
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determining, by the processor, an age of each data that has been pulled into the particular context-based conformed dimensional data gravity well; and removing from the particular context-based conformed dimensional data gravity well any data object that is older than a predetermined age.
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8. A computer program product for defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising:
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receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving a data stream of non-dimensional data objects; applying a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing the synthetic context-based object into a context-based n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed conformed dimensional object, wherein the virtual mass of the parsed conformed dimensional object is derived from a formula of;
Pd(C)×
Wtd(S),where Pd(C) is the probability that
1) said one of the non-dimensional data objects has been associated with the correct dimensional label,
2) said one of the non-dimensional data objects is uncorrupted, and
3) said one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular context-based conformed dimensional data gravity well; and
where Wtd(S) is the weighting factor of importance of the conformed dimensional object;creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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11. The computer program product of claim 8, wherein the weighting factor of importance of a data object is based on how important the data object is to a particular project.
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12. The computer program product of claim 8, further comprising program code that is readable and executable by the processor to:
determine that said one of the non-dimensional data objects is uncorrupted by determining that said one of the non-dimensional data objects is not a fragment of an original data object.
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13. The computer program product of claim 8, further comprising program code that is readable and executable by the processor to:
graphically represent said at least one dimension object and said at least one context object on a wall of said particular context-based conformed dimensional data gravity well.
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14. The computer program product of claim 8, further comprising program code that is readable and executable by the processor to:
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determine an age of each data that has been pulled into the particular context-based conformed dimensional data gravity well; and remove from the particular context-based conformed dimensional data gravity well any data object that is older than a predetermined age.
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15. A computer system comprising:
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a processor, a computer readable memory, and a non-transitory computer readable storage medium; first program instructions to receive a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; second program instructions to associate one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; third program instructions to receive a data stream of non-dimensional data objects; fourth program instructions to apply a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; fifth program instructions to parse the conformed dimensional object into a dimensional n-tuple, wherein the n-tuple comprises a pointer to said one of the non-dimensional data objects, a probability that said one of the non-dimensional data objects has been associated with a correct dimensional label, a probability that said one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; sixth program instructions to parse the synthetic context-based object into a context-based n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; seventh program instructions to calculate a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; eighth program instructions to calculate a virtual mass of a parsed conformed dimensional object, wherein the virtual mass of the parsed conformed dimensional object is derived from a formula of;
Pd(C)×
Wtd(S),where Pd(C) is the probability that
1) said one of the non-dimensional data objects has been associated with the correct dimensional label,
2) said one of the non-dimensional data objects is uncorrupted, and
3) said one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular context-based conformed dimensional data gravity well; and
where Wtd(S) is the weighting factor of importance of the conformed dimensional object;ninth program instructions to create multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; tenth program instructions to transmit multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and eleventh program instructions to define multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well; and
whereinthe first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, tenth, and eleventh program instructions are stored on the non-transitory computer readable storage medium for execution by the processor via the computer readable memory. - View Dependent Claims (16, 17, 18, 19, 20)
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18. The computer system of claim 15, wherein the weighting factor of importance of a data object is based on how important the data object is to a particular project.
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19. The computer system of claim 15, further comprising:
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twelfth program instructions to determine that said one of the non-dimensional data objects is uncorrupted by determining that said one of the non-dimensional data objects is not a fragment of an original data object; and
whereinthe twelfth program instructions are stored on the non-transitory computer readable storage medium for execution by the processor via the computer readable memory.
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20. The computer system of claim 15, further comprising:
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twelfth program instructions to determine an age of each data that has been pulled into the particular context-based conformed dimensional data gravity well; and thirteenth program instructions to remove from the particular context-based conformed dimensional data gravity well any data object that is older than a predetermined age; and
wherein the twelfth and thirteenth program instructions are stored on the non-transitory computer readable storage medium for execution by the processor via the computer readable memory.
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Specification