Method, system, and computer readable medium for detecting related subgroups of text in an electronic document

• US 9,069,754 B2
• Filed: 09/21/2011
• Issued: 06/30/2015
• Est. Priority Date: 09/29/2010
• Status: Expired due to Fees

• Current Assignee: Concert Technology Corporation
• Original Assignee: Rhonda Enterprises, LLC (Concert Technology Corporation)
• Inventors: Kandekar, Kunal, Curtis, Scott, Svendsen, Hugh
• Primary Examiner(s): TSUI, WILSON W
• Application Number:
  US13/239,367
• Publication Number:
  US 20120079372A1
• Time in Patent Office: 1,378 Days
• Field of Search: 715/209, 715/210, 715230-232, 715/243, 715/248, 715/253, 715/273, 715/277, 715/234, 715/254, 715/256, 707/723, 707/727, 707/729, 707/730, 707/736, 707/737
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 40/258 Heading extraction; Automatic titling; Numbering

Abstract

Disclosed herein are systems and methods for navigating electronic texts. According to an aspect, a method may include determining that a user non-linearly navigates between text subgroups within electronic text. The method may also include linking the text subgroups in response to determining that the user non-linearly navigates between the text subgroups. Further, for example, text subgroups within an electronic text may be determined. In this example, a similarity relationship between content of each text subgroup and one or more other text subgroups may be determined for linking the text subgroups.

Claims

1. A method comprising:

determining text subgroups within an electronic text;

determining a relevance score for each word of one or more words within each of the determined text subgroups, the relevance score based on at least one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

selecting, by an electronic device based on input received from a user, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

selecting, by the electronic device, a text seed from the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

creating a text cluster corresponding to the current user position by associating the selected text seed with the one or more adjacent determined text subgroups based on the determined first similarity relationship to the selected text seed;

determining an activity indication of times when a user has read other determined text subgroups within the electronic text;

determining a second similarity relationship between the text cluster and other text subgroups;

linking the text cluster to at least one of the determined text subgroups based on the determined second similarity relationship between the text cluster and the other determined text subgroups;

displaying in a first display area, a portion of the electronic text corresponding to the text cluster; and

displaying in a second display area, at least one of the determined text subgroups linked to the text cluster based on the determined times when the user read the other determined text subgroups.

2. The method of claim 1, wherein one or more of the linked determined text subgroups are sorted by a similarity score based on the determined similarity relationship.

3. The method of claim 1, comprising displaying a graphic as an indicator of the determined similarity relationship in an area adjacent to the display area for each determined text subgroup linked to the text cluster.

4. The method of claim 1, wherein displaying in the second display area comprises displaying in the second display area, one or more of the linked determined text subgroups positioned before the text cluster.

5. The method of claim 1, wherein displaying in the second display area comprises displaying in the second display area, one or more of the linked determined text subgroups positioned after the current text cluster.

6. The method of claim 1, wherein determining the first or second similarity relationship comprises one of performing semantic analysis, performing natural language processing, identifying causal relationships between the text seed and the text subgroups, determining semantic similarity based on ontology, using a semantic index to compare semantic similarities, and determining a statistic similarity.

7. A method comprising:

determining text subgroups within an electronic text;

determining a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

selecting, by an electronic device, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

selecting, by the electronic device, a text seed within the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

creating a text cluster by associating the text seed with the one or more adjacent determined text subgroups based on the first similarity relationship; and

for each of the determined text subgroups outside of the text cluster;

determining an activity indication of time when a user has read the determined text subgroup;

determining a second similarity relationship between content of the determined text subgroup and the text cluster; and

linking the determined text subgroup to the text cluster based on the second similarity relationship and on the determined time the user read the text subgroup.

8. The method of claim 7, wherein determining the first similarity relationship comprises determining the first similarity relationship between one of the determined text subgroups and one or more adjacent determined text subgroups based on another similarity relationship of content within each determined text subgroup.

9. The method of claim 7, wherein determining the first similarity relationship comprises determining the first similarity relationship between one of the determined text subgroups and one or more adjacent determined text subgroups based on one of chapters, paragraphs, and sentences of the electronic text.

10. The method of claim 7, wherein linking the determined text subgroup to the text cluster comprises storing a navigational aid in metadata of the electronic text that indicates association of the determined text subgroup with the text cluster.

11. The method of claim 10, further comprising presenting, for each linked determined text subgroup outside of the text cluster, a navigational link that links the linked determined text subgroup to the text cluster.

12. The method of claim 7, wherein determining the second similarity relationship comprises determining the second similarity relationship between the text cluster and the determined text subgroups positioned forward of the text cluster, and

wherein linking comprises linking the text cluster to the forward-positioned determined text subgroup having the highest second similarity relationship.

13. The method of claim 7, wherein determining the second similarity relationship comprises determining the second similarity relationship between the text cluster and the determined text subgroups positioned backward of the text cluster,

wherein linking comprises linking the text cluster to the backward-positioned determined text subgroup having the highest second similarity relationship.

14. The method of claim 7, wherein determining the second similarity relationship comprises:

using a semantic graph representing relations between words to compare words of the text cluster and words in the determined text subgroup; and

using the comparison to link the determined text subgroup with the text cluster.

15. The method of claim 14, further comprising generating the semantic graph using at least one of pre-generated summarization of the electronic text, metadata of the electronic text, semantic analysis of the electronic text, semantic indexing, natural language processing (NLP), and statistical techniques.

16. An electronic device comprising:

a hardware processor;

an electronic document manager configured to;

determine text subgroups within an electronic text;

determine a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

select, based on input received from a user, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

select, a text seed from the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determine a first similarity relationship between the selected text seed and one or more determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

create a text cluster corresponding to the current user position by associating the selected text seed with the one or more adjacent determined text subgroups based on the determined first similarity relationship to the selected text seed;

determine an activity indication of times when a user has read other determined text subgroups within the electronic text;

determining a second similarity relationship between the text cluster and other determined text subgroups

link the text cluster to at least one of the determined text subgroups based on the determined second similarity relationship between the text cluster and the other determined text subgroups; and

a user interface configured to;

display in a first display area, a portion of the electronic text corresponding to the text cluster; and

display in a second display area, at least one of the determined text subgroups linked to the text cluster based on the times when the user read the other determined text subgroups.

17. The electronic device of claim 16, wherein one or more of the linked determined text subgroups are sorted by a similarity score based on the determined similarity relationship.

18. The electronic device of claim 16, wherein the user interface is configured to display a graphic as an indicator of the determined similarity relationship in an area adjacent to the display area for each determined text subgroup linked to the text cluster.

19. The electronic device of claim 16, wherein the electronic document manager is configured to determine the first or second similarity relationship by one of performing semantic analysis, performing natural language processing, identifying causal relationships between the text seed and the text subgroups, determining semantic similarity based on ontology, using a semantic index to compare semantic similarities, and determining a statistic similarity.

20. An electronic device comprising:

a hardware processor;

an electronic document manager configured to;

determine text subgroups within an electronic text;

determine a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

select, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

select, a text seed within the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determine a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

create a text cluster by associating the text seed with the one or more adjacent determined text subgroups based on the first similarity relationship; and

for each of the determined text subgroups outside of the text cluster;

determine an activity indication of time when a user has read the determined text subgroup;

determine a second similarity relationship between content of the determined text subgroup and the text cluster; and

link the determined text subgroup to the text cluster based on the second similarity relationship and on the determined time the user read the determined text subgroup.

21. A non-transitory computer-readable storage medium having stored thereon computer executable instructions for performing the following steps:

determining text subgroups within an electronic text;

determining a relevance score for each word of one or more words within each of the determined text subgroups, the relevance score based on at least one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

selecting, by an electronic device based on input received from a user, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

selecting, by the electronic device, a text seed from the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

creating a text cluster corresponding to the current user position by associating the selected text seed with the one or more adjacent determined text subgroups based on the determined first similarity relationship to the selected text seed;

determining an activity indication of times when a user has read other determined text subgroups within the electronic text;

determining a second similarity relationship between the text cluster and other determined text subgroups;

linking the text cluster to at least one of the determined text subgroups based on the determined second similarity relationship between the text cluster and the other determined text subgroups;

displaying in a first display area, a portion of the electronic text corresponding to the text cluster; and

displaying in a second display area, at least one of the determined text subgroups linked to the text cluster based on the determined times when the user read the other determined text subgroups.

22. A non-transitory computer-readable storage medium having stored thereon computer executable instructions for performing the following steps:

determining text subgroups within an electronic text;

determining a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups;

selecting, by an electronic device, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text;

selecting, by the electronic device, a text seed within the selected text subgroup based on the relevance scores of the words within the selected text subgroup;

determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed;

creating a text cluster by associating the text seed with the one or more adjacent determined text subgroups based on the first similarity relationship; and

for each of the determined text subgroups outside of the text cluster;

determining an activity indication of time when a user has read the determined text subgroup;

determining a second similarity relationship between content of the determined text subgroup and the text cluster; and

linking the determined text subgroup to the text cluster based on the second similarity relationship and on the determined time the user read the determined text subgroup.