Method for re-ranking documents retrieved from a document database

• US 7,801,887 B2
• Filed: 10/27/2004
• Issued: 09/21/2010
• Est. Priority Date: 10/27/2004
• Status: Expired due to Fees

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Knepper, Margaret M., Frieder, Ophir, Fox, Kevin Lee
• Primary Examiner(s): Wong, Don
• Assistant Examiner(s): Brown, Sheree N
• Application Number:
  US10/974,304
• Publication Number:
  US 20060089926A1
• Time in Patent Office: 2,155 Days
• Field of Search: 707 3- 5
• US Class Current: 707/723
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing

Abstract

A computer-implemented method for processing documents in a document database includes generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query, and processing vocabulary words based upon occurrences thereof in at least some of the retrieved documents. Respective relevancies of the vocabulary words based on the occurrences thereof and the user search query are generated. A re-ranking of the retrieved documents is generated based on the relevancies of the vocabulary words.

Claims

1. A computer-implemented method for processing documents in a document database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising:

operating the processor to perform the following

generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query provided by a user;

displaying for the user the initial ranking of the retrieved documents;

permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents;

generating respective relevancies of the user-selected vocabulary words in the retrieved documents;

generating a re-ranking of the retrieved documents based on the generated respective relevancies of the vocabulary words;

selecting N top ranked documents from the retrieved documents before processing the plurality of vocabulary words, with N being an integer greater than 1; and

wherein generating the respective relevancies and generating the re-ranking are with respect to the N top-ranked documents; and

operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking.

2. A computer-implemented method according to claim 1 further comprising generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents before generating the initial ranking of retrieved documents.

3. A computer-implemented method according to claim 1 further comprising selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary.

4. A computer-implemented method according to claim 3 wherein the plurality of vocabulary words are based upon words in at least one predetermined document.

5. A computer-implemented method according to claim 4 wherein the at least one predetermined document is not part of the retrieved documents.

6. A computer-implemented method according to claim 3 further comprising adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents.

7. A computer-implemented method according to claim 6 further comprising determining a quality of the vocabulary based upon how many vocabulary words are added thereto.

8. A computer-implemented method according to claim 1 wherein generating the respective relevancies of the vocabulary words comprises:

counting how many times a respective vocabulary word is used in the N top ranked documents; and

counting how many of the N top ranked documents uses the respective vocabulary word.

9. A computer-implemented method according to claim 8 further comprising generating a word/document ratio for each respective vocabulary word based upon the counting, and if the word/document ratio is less than a threshold, then the relevancy of the word is not used when generating the re-ranking of the N top ranked documents.

10. A computer-implemented method according to claim 1 further comprising determining which documents from at least some of the retrieved documents are irrelevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the irrelevant documents.

11. A computer-implemented method according to claim 1 further comprising determining which documents from at least some of the retrieved documents are relevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the relevant documents.

12. A computer-implemented method according to claim 11 further comprising determining if the respective vocabulary words are relevant to the user search query;

and wherein determining the relevant documents is based upon the relevant vocabulary words.

13. A computer-implemented method according to claim 1 further comprising determining a respective source of at least some of the retrieved documents, and assigning priority to documents provided by preferred sources;

and wherein generating the re-ranking of the retrieved documents is also based on documents with preferred sources.

14. A computer-implemented method according to claim 1 further comprising generating a second re-ranking of the retrieved documents based upon a combination of the initial ranking and the re-ranking of the retrieved documents.

15. A computer-implemented method according to claim 1 further comprising displaying the re-ranked documents.

16. A computer-implemented method for processing documents in a document database, the documents having an initial ranking based upon a user search query provided by a user using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising:

operating the processor to perform the following

selecting N top ranked documents from the retrieved documents, with N being an integer greater than 1;

displaying for the user the initial ranking of the N top ranked retrieved documents;

permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents, with at least one of the vocabulary words not being in the user search query;

generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved documents based on

counting how many times a respective vocabulary word is used in the N top ranked documents; and

counting how many of the N top ranked documents uses the respective vocabulary word;

generating a re-ranking of the N top ranked documents based on the relevancies of the vocabulary words; and

operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking.

17. A computer-implemented method according to claim 16 further comprising generating the plurality of vocabulary words based upon occurrences thereof in the N top ranked documents.

18. A computer-implemented method according to claim 16 further comprising selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary.

19. A computer-implemented method according to claim 18 wherein the plurality of vocabulary words are based upon words in at least one predetermined document.

20. A computer-implemented method according to claim 19 wherein the at least one predetermined document is not part of the retrieved documents.

21. A computer-implemented method according to claim 19 further comprising adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents.

22. A computer-implemented method according to claim 21 further comprising determining a quality of the vocabulary based upon how many vocabulary words are added thereto.

23. A computer-implemented method according to claim 16 further comprising generating a word/document ratio for each respective vocabulary word based upon the counting, and if the word/document ratio is less than a threshold, then the relevancy of the word is not used when generating the re-ranking of the N top ranked documents.

24. A computer-implemented method according to claim 16 further comprising determining which documents from at least some of the retrieved documents are irrelevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the irrelevant documents.

25. A computer-implemented method according to claim 16 further comprising determining which documents from the N top ranked documents are relevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the relevant documents.

26. A computer-implemented method according to claim 25 further comprising determining if the respective vocabulary words are relevant to the user search query;

and wherein determining the relevant documents is based upon the relevant vocabulary words.

27. A computer-implemented method according to claim 16 further comprising determining a respective source of the N top ranked documents, and assigning priority to documents provided by preferred sources;

and wherein generating the re-ranking of the N top ranked documents is also based on documents with preferred sources.

28. A computer-implemented method according to claim 16 further comprising generating a second re-ranking of the N top ranked documents based upon a combination of the initial ranking and the re-ranking of the N top ranked documents.

29. A computer-readable medium having stored thereon a data structure for processing documents in a document database, the computer-readable medium comprising:

a first data field for generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query provided by a user;

a second data field for displaying to the user the initial ranking of the retrieved documents;

a third data field for permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents;

a fourth data field for generating respective relevancies of the user-selected vocabulary words;

a fifth data field for generating a re-ranking of the retrieved documents based on the generated respective relevancies of the vocabulary words;

a sixth data field for displaying for the user the re-ranking of the documents, and for each document being displayed, also displaying its initial ranking; and

a seventh data field for generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents before generating the initial ranking of retrieved documents.

30. A computer-readable medium according to claim 29 further comprising an eighth data field for selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary, the plurality of vocabulary words corresponding to the user search topic.

31. A computer-readable medium according to claim 30 wherein the plurality of vocabulary words are based upon words in at least one predetermined document.

32. A computer-readable medium according to claim 31 wherein the at least one predetermined document is not part of the retrieved documents.

33. A computer-readable medium according to claim 31 further comprising a ninth data field for adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents.

34. A computer-readable medium according to claim 33 further comprising a tenth data field for determining a quality of the vocabulary based upon how many vocabulary words are added thereto.

35. A computer-readable medium according to claim 29 further comprising an eleventh data field for selecting N top ranked documents from the retrieved documents before processing the plurality of vocabulary words, with N being an integer greater than 1;

and wherein generating the respective relevancies in said third data field and generating the re-ranking in said fourth data field are with respect to the N top-ranked documents.

36. A computer-readable medium according to claim 35 wherein generating the respective relevancies of the vocabulary words comprises:

a twelfth data field for counting how many times a respective vocabulary word is used in the N top ranked documents; and

a thirteenth data field for counting how many of the N top ranked documents uses the respective vocabulary word.

37. A computer-readable medium according to claim 36 further comprising a fourteenth data field for generating a word/document ratio for each respective vocabulary word based upon the counting, and if the word/document ratio is less than a threshold, then the relevancy of the word is not used when generating the re-ranking of the N top ranked documents.

38. A computer-readable medium according to claim 29 further comprising a fifteenth data field for determining which documents from at least some of the retrieved documents are relevant to the user search query;

and wherein generating the re-ranking of the retrieved documents in said fourth data field is also based on the relevant documents.

39. A computer-readable medium according to claim 38 further comprising a sixteenth data field for determining if the respective vocabulary words are relevant to the user search query;

and wherein determining the relevant documents in said third data field is based upon the relevant vocabulary words.

40. A computer-readable medium according to claim 29 further comprising a seventeenth data field for determining a respective source of at least some of the retrieved documents, and assigning priority to documents provided by preferred sources;

and wherein generating the re-ranking of the retrieved documents in said fourth data field is also based on documents with preferred sources.

41. A computer-readable medium according to claim 29 further comprising an eighteenth data field for generating a second re-ranking of the retrieved documents based upon a combination of the initial ranking and the re-ranking of the retrieved documents.

42. A computer-readable medium according to claim 29 further comprising a nineteenth data field for displaying the re-ranked documents.

43. A computer implemented system for processing documents in a document database comprising:

an input for receiving a user search query provided by a user; and

a processor coupled to said input and configured for performing the following

generating an initial ranking of retrieved documents from the document database using an information retrieval system and based upon the user search query;

permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents;

generating respective relevancies of the user-selected vocabulary words based on the occurrences thereof and the user search query;

generating a re-ranking of the retrieved documents based on the relevancies of the vocabulary words;

said processor is further configured for selecting N top ranked documents from the retrieved documents before processing the plurality of vocabulary words, with N being an integer greater than 1; and

wherein generating the respective relevancies and generating the re-ranking are with respect to the N top-ranked documents; and

a display coupled to said processor for displaying the re-ranked documents, and for each document being re-ranked, also displaying its initial ranking.

44. A computer implemented system according to claim 43 wherein said processor is further configured for generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents before generating the initial ranking of retrieved documents.

45. A computer implemented system according to claim 43 wherein said processor is further configured for selecting a vocabulary comprising the plurality of vocabulary words before permitting user selection of the plurality of vocabulary.

46. A computer implemented system according to claim 45 wherein the plurality of vocabulary words are based upon words in at least one predetermined document.

47. A computer implemented system according to claim 46 wherein the at least one predetermined document is not part of the retrieved documents.

48. A computer implemented system according to claim 46 wherein said processor is further configured for adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents.

49. A computer implemented system according to claim 48 wherein said processor is further configured for determining a quality of the vocabulary based upon how many vocabulary words are added thereto.

50. A computer implemented system according to claim 43 wherein generating the respective relevancies of the vocabulary words comprises:

counting how many times a respective vocabulary word is used in the N top ranked documents; and

counting how many of the N top ranked documents uses the respective vocabulary word.

51. A computer implemented system according to claim 50 wherein said processor is further configured for generating a word/document ratio for each respective vocabulary word based upon the counting, and if the word/document ratio is less than a threshold, then the relevancy of the word is not used when generating the re-ranking of the N top ranked documents.

52. A computer implemented system according to claim 43 wherein said processor is further configured for determining which documents from at least some of the retrieved documents are irrelevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the irrelevant documents.

53. A computer implemented System according to claim 43 wherein said processor is further configured for determining which documents from at least some of the retrieved documents are relevant to the user search query;

and wherein generating the re-ranking of the retrieved documents is also based on the relevant documents.

54. A computer implemented system according to claim 53 wherein said processor is further configured for determining if the respective vocabulary words are relevant to the user search query;

and wherein determining the relevant documents is based upon the relevant vocabulary words.

55. A computer implemented system according to claim 43 wherein said processor is further configured for determining a respective source of at least some of the retrieved documents, and assigning priority to documents provided by preferred sources;

and wherein generating the re-ranking of the retrieved documents is also based on documents with preferred sources.

56. A computer implemented system according to claim 43 wherein said processor is further configured for generating a second re-ranking of the retrieved documents based upon a combination of the initial ranking and the re-ranking of the retrieved documents.