System and method for analyzing and categorizing text

• US 9,405,733 B1
• Filed: 03/09/2012
• Issued: 08/02/2016
• Est. Priority Date: 12/18/2007
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Stanton, Aaron, Zehm, Brandon, Kreiner, Paul
• Primary Examiner(s): Huynh, Cong-Lac
• Application Number:
  US13/416,996
• Time in Patent Office: 1,607 Days
• Field of Search: 715/256, 715/200
• US Class Current: 1/1
• CPC Class Codes: G06F 16/31 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/9562 Bookmark management
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 40/10 Text processing natural language analysis G06F40/20; semantic analysis G06F40/30; processing or translation of natural language G06F40/40
• CPC Class Codes: G06F 40/279 Recognition of textual entities
• CPC Class Codes: G06V 30/224 of printed characters having additional code marks or containing code marks

Abstract

A system and method are provided for analyzing elements of text for comparative purposes. Text is provided to the system in an electronic format readable by the system. The system divides the text data into scenes, which may then be compared against a range of various values across a database of scenes from different texts. Data from one text can be used to identify other texts with similar styles, or identify texts with different styles, and to rank those differences on a spectrum. The system may use data from one text to identify other texts that a user may like, and present information about the text to the user in various forms.

Claims

1. A method comprising:

obtaining a first text comprising a plurality of characters, the first text selected by a first user;

partitioning the first text into a plurality of scenes, wherein each scene comprises a unique set of one or more contiguous characters included in the first text;

determining, for each scene from the set of scenes, a score based on one or more predetermined metrics;

determining, based on the score for each score in the set of scenes, a cumulative score for the first text;

selecting a second text to recommend to the first user based on the cumulative score of the first text and a cumulative score of the second text; and

transmitting, to a remote computer of the first user, data recommending the second text.

2. The method of claim 1, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

identifying from the unique set of one or more contiguous characters in the scene, a number of sentences in the scene that are between an opening quotation mark and a closing quotation mark.

3. The method of claim 1, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a total number of words in the scene.

4. The method of claim 1, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a number of adverbs in the scene.

5. The method of claim 1, wherein determining the cumulative score for the first text comprises calculating a mean value from at least two scores.

6. The method of claim 1, further comprising:

determining an acceptable threshold value range.

7. The method of claim 6, wherein selecting the second text further comprises:

determining, based on the acceptable threshold value range that the cumulative score of the second text is within an upper threshold limit and a lower threshold limit of the cumulative score of the first text.

8. A non-transitory computer-readable medium including instructions that, when executed by one or more computer processors of a computing device, cause the computing device to:

obtain a first text comprising a plurality of characters, the first text selected by a first user;

partition the first text into a plurality of scenes, wherein each scene comprises a unique set of one or more contiguous characters included in the first text;

determine, for each scene from the set of scenes, a score based on one or more predetermined metrics;

determine, based on the scores for each scene in the set of scenes, a cumulative score for the first text;

receive a user preference, the user preference including a predefined range of acceptable cumulative score deviations;

select a second text to recommend to the first user based on the cumulative score of the first text, a cumulative score of the second text, and the user preference; and

transmit, to a remote computer of the first user, data recommending the second text.

9. The non-transitory computer-readable medium of claim 8, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

identifying from the unique set of one or more contiguous characters in the scene, a number of sentences in the scene that are between an opening quotation mark and a closing quotation mark.

10. The non-transitory computer-readable medium of claim 8, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a total number of words in the scene.

11. The non-transitory computer-readable medium of claim 8, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a number of adverbs in the scene.

12. The non-transitory computer-readable medium of claim 8, wherein determining the cumulative score for the first text comprises calculating a mean value from at least two scores.

13. The non-transitory computer-readable medium of claim 8, wherein the instructions further cause the computing device to:

determine an acceptable threshold value range.

14. The non-transitory computer-readable medium of claim 13, wherein selecting the second text further comprises:

determining, based on the acceptable threshold value range that the cumulative score of the second text is within an upper threshold limit and a lower threshold limit of the cumulative score of the first text.

15. A system comprising:

one or more computer processors; and

a memory containing instructions that, when executed by the one or more computer processor, cause the system to;

obtain a first text comprising a plurality of characters, the first text selected by a first user;

partition the first text into a plurality of scenes, wherein each scene comprises a unique set of one or more contiguous characters included in the first text;

determine, for each scene from the set of scenes, a score based on one or more predetermined metrics;

determine, based on the score for each scene in the set of scenes, a cumulative score for the first text;

receive a user preference, the user preference including a predefined range of acceptable cumulative score deviations;

select a second text to recommend to the first user based on the cumulative score of the first text, a cumulative score of the second text, and the user preference, wherein the cumulative score of the second text is within the predefined range of acceptable cumulative score deviations; and

transmit, to a remote computer of the first user, data recommending the second text.

16. The system of claim 15, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

identifying from the unique set of one or more contiguous characters in the scene, a number of sentences in the scene that are between an opening quotation mark and a closing quotation mark.

17. The system of claim 15, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a total number of words in the scene.

18. The system of claim 15, wherein determining the score for a scene based on the one or more predetermined metrics comprises:

determining a ratio of a number of verbs in the scene to a number of adverbs in the scene.

19. The system of claim 15, wherein determining the cumulative score for the first text comprises calculating a mean value from at least two scores.

20. The system of claim 15, wherein the instructions further cause the system to determine an acceptable threshold value range, wherein selecting the second text further comprises:

determining, based on the acceptable threshold value range that the cumulative score of the second text is within an upper threshold limit and a lower threshold limit of the cumulative score of the first text.