Method and apparatus for processing metadata

• US 8,156,123 B2
• Filed: 04/22/2005
• Issued: 04/10/2012
• Est. Priority Date: 06/25/2004
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Tribble, Guy L., Arrouye, Yan, Giampaolo, Dominic
• Primary Examiner(s): SYED, FARHAN M
• Application Number:
  US11/112,955
• Publication Number:
  US 20050289111A1
• Time in Patent Office: 2,545 Days
• Field of Search: None
• US Class Current: 707/739
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/90335 Query processing

Abstract

Methods and apparatuses for processing metadata are described herein. In one embodiment, when a file (e.g., a text, audio, and/or image files) having metadata is received, the metadata and optionally at least a portion of the content of the file are extracted from the file to generate a first set of metadata. An analysis is performed on the extracted metadata and the content to generate a second set of metadata, which may include metadata in addition to the first set of metadata. The second set of metadata may be stored in a database suitable to be searched to identify or locate the file. Other methods and apparatuses are also described.

Claims

1. A computer-implemented method, comprising:

receiving, using one or more processors, one or more files at a client, wherein each file includes content and metadata;

extracting, using the one or more processors, the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating, using the one or more processors, a first metadata set using the extracted metadata and content;

analyzing, using the one or more processors, the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

using the one or more processors, one or more external resources to determine additional image metadata or audio metadata, wherein the additional metadata is determined based upon the metadata from with the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files;

generating, using the one or more processors, a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set; and

performing, using the one or more processors, a system-wide search at the client for a particular file.

2. The method of claim 1, wherein the text metadata importer extracts keywords using tokenization, stemming, or concept extraction techniques.

3. The method of claim 1, wherein analyzing the first set of metadata includes recognizing text within an image or within an audio segment to extract additional image metadata for the image or audio metadata for the audio segment.

4. The method of claim 1, further comprising:

storing, using the one or more processing units, the second metadata set in an indexed database under one or more searchable categories.

5. The method of claim 1, wherein the particular file includes a combination of text metadata, image metadata, and audio metadata.

6. The method of claim 1, wherein analyzing the first metadata set includes using one or more analytical techniques.

7. The method of claim 6, wherein the one or more analytical techniques include Latent semantic analysis (LSA), tokenization, stemming, concept extraction, spectrum analysis and filtering, optical character recognition (OCR), and voice recognition.

8. The method of claim 1, wherein performing text analysis includes generating one or more keywords using tokenization, stemming, or concept extraction, and wherein the one or more keywords and Latent semantic analysis (LSA) are used to generate the second metadata set.

9. The method of claim 1, wherein performing image analysis includes using spectrum analysis or spectrum filtering to determine an image generation time and configuration.

10. The method of claim 1, wherein the one or more external resources include a global positioning system (GPS), and wherein performing image analysis includes using the GPS to determine image generation geography.

11. The method of claim 1, wherein performing audio analysis includes determining whether the audio clip includes music, a particular song, or a recorded voice.

12. The method of claim 11, wherein performing audio analysis includes determining a type of music and one or more musical instruments using a frequency analysis, and wherein the frequency analysis includes spectrum analysis or spectrum filtering.

13. The method of claim 11, wherein performing audio analysis includes recognizing one or more words using voice recognition, and wherein the one or more words and Latent semantic analysis (LSA) are used to generate the second metadata set.

14. The method of claim 1, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

15. The method of claim 1, wherein generating the second metadata set includes analyzing text metadata having no common words.

16. The method of claim 1, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

17. The method of claim 1, wherein generating the second metadata set includes using a relevancy test.

18. The method of claim 1, wherein performing the system-wide search includes generating data for displaying a set of search results, wherein the set of search results is formatted into one or more categories, and wherein each category includes one or more headers.

19. The method of claim 18, wherein the one or more categories include date, kind, or people.

20. The method of claim 18, wherein the one or more headers indicate one or more types of files in the set of search results.

21. The method of claim 18, wherein the one or more headers facilitate searching the set of search results.

22. The method of claim 18, wherein the set of search results can be reformatted, and wherein reformatting the set of search results includes reorganizing the set of search results into one or more different categories, each category having one or more different headers.

23. The method of claim 22, wherein the one or more different categories include date, kind, or people.

24. The method of claim 22, wherein the one or more different headers indicate one or more types of files in the set of search results.

25. The method of claim 22, wherein the one or more different headers facilitate searching the set of search results.

26. The method of claim 18, wherein the set of search results is displayable in one or more views, including a list view and an icon view.

27. The method of claim 26, wherein the one or more views are concurrently displayable.

28. The method of claim 18, wherein when the set of search results is abbreviated, an interactive indicator is displayed, and wherein activating the interactive indicator generates data for displaying additional search results in the set of search results.

29. A system, comprising:

one or more processors;

a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including;

receiving one or more files at a client, wherein each file includes content and metadata;

extracting the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating a first metadata set using the extracted metadata and content;

analyzing the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

using one or more external resources to determine additional image metadata or audio metadata, wherein the additional metadata is determined based upon the metadata from the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files;

generating a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set; and

performing a system-wide search at the client for a particular file.

30. The system of claim 29, wherein the text metadata importer extracts keywords using tokenization, stemming, or concept extraction techniques.

31. The system of claim 29, wherein analyzing the first set of metadata includes recognizing text within an image or within an audio segment to extract additional image metadata for the image or audio metadata for the audio segment.

32. The system of claim 29, further comprising instructions configured to cause the one or more processors to perform operations, including:

storing the second metadata set in an indexed database under one or more searchable categories.

33. The system of claim 29, wherein the particular file includes a combination of text metadata, image metadata, and audio metadata.

34. The system of claim 29, wherein analyzing the first metadata set includes using one or more analytical techniques.

35. The system of claim 34, wherein the one or more analytical techniques include Latent semantic analysis (LSA), tokenization, stemming, concept extraction, spectrum analysis and filtering, optical character recognition (OCR), and voice recognition.

36. The system of claim 29, wherein performing image analysis includes using spectrum analysis or spectrum filtering to determine an image generation time and configuration.

37. The system of claim 29, wherein the one or more external resources include a global positioning system (GPS), and wherein performing image analysis includes using the GPS to determine image generation geography.

38. The system of claim 29, wherein performing audio analysis includes determining whether the audio clip includes music, a particular song, or a recorded voice.

39. The system of claim 38, wherein performing audio analysis includes determining a type of music and one or more musical instruments using a frequency analysis, and wherein the frequency analysis includes spectrum analysis or spectrum filtering.

40. The system of claim 38, wherein performing audio analysis includes recognizing one or more words using voice recognition, and wherein the one or more words and Latent semantic analysis (LSA) are used to generate the second metadata set.

41. The system of claim 29, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

42. The system of claim 29, wherein generating the second metadata set includes analyzing text metadata having no common words.

43. The system of claim 29, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

44. The system of claim 29, wherein generating the second metadata set includes using a relevancy test.

45. A computer-program product, embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus, comprising:

one or more processors;

a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including;

receiving one or more files at a client, wherein each file includes content and metadata;

extracting the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating a first metadata set using the extracted metadata and content;

analyzing the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

using one or more external resources to determine additional image metadata or audio metadata, wherein the additional metadata is determined based upon the metadata from the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files;

generating a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set; and

performing a system-wide search at the client for a particular file.

46. The computer-program product of claim 45, wherein the text metadata importer extracts keywords using tokenization, stemming, or concept extraction techniques.

47. The computer-program product of claim 45, wherein analyzing the first set of metadata includes recognizing text within an image or within an audio segment to extract additional image metadata for the image or audio metadata for the audio segment.

48. The computer-program product of claim 45, further comprising instructions configured to cause a data processing apparatus to:

store the second metadata set in an indexed database under one or more searchable categories.

49. The computer-program product of claim 45, wherein the particular file includes a combination of text metadata, image metadata, and audio metadata.

50. The computer-program product of claim 45, wherein analyzing the first metadata set includes using one or more analytical techniques.

51. The computer-program product of claim 50, wherein the one or more analytical techniques include Latent semantic analysis (LSA), tokenization, stemming, concept extraction, spectrum analysis and filtering, optical character recognition (OCR), and voice recognition.

52. The computer-program product of claim 45, wherein performing image analysis includes using spectrum analysis or spectrum filtering to determine an image generation time and configuration.

53. The computer-program product of claim 45, wherein the one or more external resources include a global positioning system (GPS), and wherein performing image analysis includes using the GPS to determine image generation geography.

54. The computer-program product of claim 45, wherein performing audio analysis includes determining whether the audio clip includes music, a particular song, or a recorded voice.

55. The computer-program product of claim 54, wherein performing audio analysis includes determining a type of music and one or more musical instruments using a frequency analysis, and wherein the frequency analysis includes spectrum analysis or spectrum filtering.

56. The computer-program product method of claim 54, wherein performing audio analysis includes recognizing one or more words using voice recognition, and wherein the one or more words and Latent semantic analysis (LSA) are used to generate the second metadata set.

57. The computer-program product of claim 45, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

58. The computer-program product of claim 45, wherein generating the second metadata set includes analyzing text metadata having no common words.

59. The computer-program product of claim 45, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

60. The computer-program product of claim 45, wherein generating the second metadata set includes using a relevancy test.

61. A computer-implemented method, comprising:

receiving, using one or more processors, one or more files at a client, wherein each file includes content and metadata;

extracting, using the one or more processors, the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating, using the one or more processors, a first metadata set using the extracted metadata and content;

analyzing, using the one or more processors, the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio, wherein the image analysis includes recognizing text within an image to extract additional image metadata, and wherein the audio analysis includes recognizing text within an audio segment to extract additional audio metadata;

generating, using the one or more processors, a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set, wherein the additional metadata is determined based upon the metadata from the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files; and

performing, using the one or more processors, a system-wide search at the client for a particular file.

62. The method of claim 61, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

63. The method of claim 61, wherein generating the second metadata set includes analyzing text metadata having no common words.

64. The method of claim 61, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

65. The method of claim 61, wherein generating the second metadata set includes using a relevancy test.

66. A system, comprising:

one or more processors;

a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including;

receiving one or more files at a client, wherein each file includes content and metadata;

extracting the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating a first metadata set using the extracted metadata and content;

analyzing the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio, wherein the image analysis includes recognizing text within an image to extract additional image metadata, and wherein the audio analysis includes recognizing text within an audio segment to extract additional audio metadata;

generating, a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set, wherein the additional metadata is determined based upon the metadata from the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files; and

performing a system-wide search at the client for a particular file.

67. The system of claim 66, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

68. The system of claim 66, wherein generating the second metadata set includes analyzing text metadata having no common words.

69. The system of claim 66, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

70. The system of claim 66, wherein generating the second metadata set includes using a relevancy test.

71. A computer-program product, embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to:

receive one or more files at a client, wherein each file includes content and metadata;

extract the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generate a first metadata set using the extracted metadata and content;

analyze the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio, wherein the image analysis includes recognizing text within an image to extract additional image metadata, and wherein the audio analysis includes recognizing text within an audio segment to extract additional audio metadata;

generate, a second metadata set using the analysis of the first metadata set and the additional metadata, wherein the second metadata set includes metadata not contained in the first metadata set, wherein the additional metadata is determined based upon the metadata from the one or more files or at least a portion of the content from the one or more files, and wherein the additional metadata does not exist in the first metadata set generated using the extracted metadata and content from the one or more files; and

performing a system-wide search at the client for a particular file.

72. The computer-program product of claim 71, wherein the metadata in the second metadata set that is not contained in the first metadata set is semantically related to the first metadata set.

73. The computer-program product of claim 71, wherein generating the second metadata set includes analyzing text metadata having no common words.

74. The computer-program product of claim 71, wherein generating the second metadata set includes analyzing the first metadata set against a previously trained metadata set.

75. The computer-program product of claim 71, wherein generating the second metadata set includes using a relevancy test.

76. A method, comprising:

receiving, using one or more processing units, one or more files at a client, wherein each file includes content and metadata, and wherein one or more files within the one or more files include a combination of text metadata, image metadata, and audio metadata;

extracting, using the one or more processing units, the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating, using the one or more processing units, a first metadata set using the extracted metadata and content;

analyzing, using the one or more processing units, the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

generating, using the one or more processing units, a second metadata set using the analysis of the first metadata set, wherein the second metadata set includes metadata not contained in the first metadata set; and

performing, using the one or more processing units, a system-wide search at the client for a particular file.

77. A system, comprising:

one or more processors;

a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including;

receiving one or more files at a client, wherein each file includes content and metadata, and wherein one or more files within the one or more files include a combination of text metadata, image metadata, and audio metadata;

extracting the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generating a first metadata set using the extracted metadata and content;

analyzing the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

generating a second metadata set using the analysis of the first metadata set, wherein the second metadata set includes metadata not contained in the first metadata set; and

performing a system-wide search at the client for a particular file.

78. A computer-program product, embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to:

receive one or more files at a client, wherein each file includes content and metadata, and wherein one or more files within the one or more files include a combination of text metadata, image metadata, and audio metadata;

extract the metadata and content from the one or more files using a text metadata importer for a file that includes text, using an image metadata importer for a file that includes an image, and using an audio metadata importer for a file that includes audio;

generate a first metadata set using the extracted metadata and content;

analyze the first metadata set by performing text analysis on text, by performing image analysis on images, and by performing audio analysis on audio;

generate a second metadata set using the analysis of the first metadata set, wherein the second metadata set includes metadata not contained in the first metadata set; and

perform a system-wide search at the client for a particular file.