Method and system for scoring texts

• US 9,471,644 B2
• Filed: 12/29/2014
• Issued: 10/18/2016
• Est. Priority Date: 09/18/2009
• Status: Active Grant

• Current Assignee: Lexxe Pty Ltd
• Original Assignee: Lexxe Pty Ltd
• Inventors: Qiao, Hong Liang
• Primary Examiner(s): NGUYEN, PHONG H
• Application Number:
  US14/585,074
• Publication Number:
  US 20150379015A1
• Time in Patent Office: 659 Days
• Field of Search: 707/722, 707/723, 707/748, 707/754
• US Class Current: 1/1
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/3346 using probabilistic model
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results

Abstract

A computer-implemented method, computer-readable medium and system for scoring a text are disclosed. Themes within one or more texts may be determined and used to score each text, where an overall score for each text may indicate a respective importance and/or value of each text. The score for each text may be determined based upon a number of themes, type of themes, frequency of theme elements associated with the themes, distribution of theme elements associated with the themes, location of themes in the text, some combination thereof, etc. In this manner, the importance or value of one or more texts may be determined more accurately using information within each text with reduced reliance upon external information. Additionally, more relevant search results can be returned to a user by using internal information to perform ranking operations and/or filtering operations associated with a search.

Claims

1. A computer implemented method of scoring a text, said method comprising:

determining a plurality of themes associated with a plurality of portions of said text, wherein each portion of said plurality of portions comprises at least one respective character;

assigning a plurality of scores to said plurality of themes, wherein each score of said plurality of scores corresponds to a respective theme of said plurality of themes; and

determining an overall score for said text based on said plurality of scores, wherein said determining said plurality of themes further comprises;

determining at least one theme element associated with a portion of said plurality of portions;

if a distribution of a plurality of instances of said at least one theme element falls within a predetermined range and if a first instance of said portion is located toward a beginning of said text and if a second instance of said portion is located toward an end of said text, associating said portion with a major theme; and

if said distribution of said plurality of instances of said at least one theme element does not fall within said predetermined range, associating said portion with a minor theme.

2. The method of claim 1, wherein said text is selected from a group consisting of a webpage, an electronic document, and an electronic book.

3. The method of claim 1 further comprising:

determining said plurality of portions of said text using phrase chunking.

4. The method of claim 1, wherein said determining said plurality of themes further comprises:

if a distribution of a plurality of instances of a portion of said plurality of portions falls within a predetermined range and if a major theme is associated with at least one other portion of said text, associating said portion with a complementary theme.

5. The method of claim 1, wherein said assigning a plurality of scores further comprises determining a respective score for each theme based on an attribute selected from a group consisting of a respective frequency of a respective plurality of instances of at least one theme element for each theme in said text, a respective distribution of a respective plurality of instances of at least one theme element for each theme in said text, and at least one respective location of each theme in said text.

6. The method of claim 1 further comprising:

accessing a search query submitted by a user;

performing a search of at least one webpage based on said search query to generate search results, wherein said search results comprise said text; and

ranking said search results based on respective overall scores of said search results.

7. The method of claim 6, wherein said ranking further comprises ranking said search results based on a number and type of respective themes, associated with each of said search results, in said search query.

8. The method of claim 6 further comprising:

filtering said search results based on a respective overall score of each of said search results, wherein said filtering further comprises filtering said search results to identify at least one search result.

9. The method of claim 6 further comprising:

ranking said at least one webpage based on a respective overall score of each of said at least one webpage.

10. The method of claim 6 further comprising:

filtering a plurality of webpages based on a respective overall score of each of said plurality of webpages, wherein said filtering further comprises filtering said plurality of webpages to identify said at least one webpage.

11. A non-transitory computer-readable medium having computer-readable program code embodied therein for causing a computer system to perform a method of scoring a text, said method comprising:

determining a plurality of themes associated with a plurality of portions of said text, wherein each portion of said plurality of portions comprises at least one respective character;

assigning a plurality of scores to said plurality of themes, wherein each score of said plurality of scores corresponds to a respective theme of said plurality of themes; and

determining an overall score for said text based on said plurality of scores, wherein said determining said plurality of themes further comprises;

determining at least one theme element associated with a portion of said plurality of portions;

if a distribution of a plurality of instances of said at least one theme element falls within a predetermined range and if a first instance of said portion is located toward a beginning of said text and if a second instance of said portion is located toward an end of said text, associating said portion with a major theme; and

if said distribution of said plurality of instances of said at least one theme element does not fall within said predetermined range, associating said portion with a minor theme.

12. The non-transitory computer-readable medium of claim 11, wherein said text is selected from a group consisting of a webpage, an electronic document, and an electronic book.

13. The non-transitory computer-readable medium of claim 11, wherein said method further comprises:

determining said plurality of portions of said text using phrase chunking.

14. The non-transitory computer-readable medium of claim 11, wherein said determining said plurality of themes further comprises:

if a distribution of a plurality of instances of a portion of said plurality of portions falls within a predetermined range and if a major theme is associated with at least one other portion of said text, associating said portion with a complementary theme.

15. The non-transitory computer-readable medium of claim 11, wherein said assigning a plurality of scores further comprises determining a respective score for each theme based on an attribute selected from a group consisting of a respective frequency of a respective plurality of instances of at least one theme element for each theme in said text, a respective distribution of a respective plurality of instances of at least one theme element for each theme in said text, and at least one respective location of each theme in said text.

16. The non-transitory computer-readable medium of claim 11, wherein said method further comprises:

accessing a search query submitted by a user;

performing a search of at least one webpage based on said search query to generate search results, wherein said search results comprise said text; and

ranking said search results based on respective overall scores of said search results.

17. The non-transitory computer-readable medium of claim 16, wherein said ranking further comprises ranking said search results based on a number and type of respective themes, associated with each of said search results, in said search query.

18. The non-transitory computer-readable medium of claim 16, wherein said method further comprises:

filtering said search results based on a respective overall score of each of said search results, wherein said filtering further comprises filtering said search results to identify at least one search result.

19. The non-transitory computer-readable medium of claim 16, wherein said method further comprises:

ranking said at least one webpage based on a respective overall score of each of said at least one webpage.

20. The non-transitory computer-readable medium of claim 16, wherein said method further comprises:

filtering a plurality of webpages based on a respective overall score of each of said plurality of webpages, wherein said filtering further comprises filtering said plurality of webpages to identify said at least one webpage.

21. A system comprising a processor and a memory, wherein said memory comprises instructions that when executed by said system implement a method of scoring a text, said method comprising:

determining a plurality of themes associated with a plurality of portions of said text, wherein each portion of said plurality of portions comprises at least one respective character;

assigning a plurality of scores to said plurality of themes, wherein each score of said plurality of scores corresponds to a respective theme of said plurality of themes; and

determining an overall score for said text based on said plurality of scores, wherein said determining said plurality of themes further comprises;

determining at least one theme element associated with a portion of said plurality of portions;

if a distribution of a plurality of instances of said at least one theme element falls within a predetermined range and if a first instance of said portion is located toward a beginning of said text and if a second instance of said portion is located toward an end of said text, associating said portion with a major theme; and

if said distribution of said plurality of instances of said at least one theme element does not fall within said predetermined range, associating said portion with a minor theme.

22. The system of claim 21, wherein said text is selected from a group consisting of a webpage, an electronic document, and an electronic book.

23. The system of claim 21, wherein said method further comprises:

determining said plurality of portions of said text using phrase chunking.

24. The system of claim 21, wherein said determining said plurality of themes further comprises:

if a distribution of a plurality of instances of a portion of said plurality of portions falls within a predetermined range and if a major theme is associated with at least one other portion of said text, associating said portion with a complementary theme.

25. The system of claim 21, wherein said assigning a plurality of scores further comprises determining a respective score for each theme based on an attribute selected from a group consisting of a respective frequency of a respective plurality of instances of at least one theme element for each theme in said text, a respective distribution of a respective plurality of instances of at least one theme element for each theme in said text, and at least one respective location of each theme in said text.

26. The system of claim 21, wherein said method further comprises:

accessing a search query submitted by a user;

performing a search of at least one webpage based on said search query to generate search results, wherein said search results comprise said text; and

ranking said search results based on respective overall scores of said search results.

27. The system of claim 26, wherein said ranking further comprises ranking said search results based on a number and type of respective themes, associated with each of said search results, in said search query.

28. The system of claim 26, wherein said method further comprises:

filtering said search results based on a respective overall score of each of said search results, wherein said filtering further comprises filtering said search results to identify at least one search result.

29. The system of claim 26, wherein said method further comprises:

ranking said at least one webpage based on a respective overall score of each of said at least one webpage.

30. The system of claim 26, wherein said method further comprises:

filtering a plurality of webpages based on a respective overall score of each of said plurality of webpages, wherein said filtering further comprises filtering said plurality of webpages to identify said at least one webpage.