Systems and methods for navigating electronic texts

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.

What is claimed: 
     
         1 . A method comprising:
 determining that a user non-linearly navigates between text subgroups within electronic text; and   in response to determining that the user non-linearly navigates between the text subgroups, linking the text subgroups.   
     
     
         2 . The method of  claim 1 , wherein the text subgroups are defined according to one of chapters, paragraphs, and sentences of the electronic text. 
     
     
         3 . The method of  claim 1 , wherein linking the text subgroups comprises storing a navigational aid in metadata of the electronic text that indicates association of the text subgroups. 
     
     
         4 . The method of  claim 3 , further comprising presenting a navigational link that links the text subgroups to one another. 
     
     
         5 . The method of  claim 1 , further comprising presenting at least one navigation link corresponding to the linked subgroups. 
     
     
         6 . A method comprising:
 determining a current user position within an electronic text;   determining a current text subgroup corresponding to the current user position;   displaying in a first display area, a portion of the electronic text corresponding to the current text subgroup; and   displaying in a second display area, one or more related text subgroups.   
     
     
         7 . The method of  claim 6 , wherein the one or more text subgroups are sorted by similarity score between each corresponding text subgroup and the current text subgroup. 
     
     
         8 . The method of  claim 6 , comprising displaying a graphic as an indicator of similarity in an area adjacent to the display area for each corresponding related text subgroup. 
     
     
         9 . The method of  claim 6 , wherein displaying in the second display area comprises displaying in the second display area, one or more related text subgroups positioned before the current text subgroup. 
     
     
         10 . The method of  claim 6 , wherein displaying in the second display area comprises displaying in the second display area, one or more related text subgroups positioned after the current text subgroup. 
     
     
         11 . The method of  claim 6 , wherein determining text subgroups related to the current text subgroup corresponding to the current user position 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. 
     
     
         12 . A method comprising:
 determining text subgroups within an electronic text; and   for each text subgroup:
 determining a similarity relationship between content of the text subgroup and one or more other text subgroups; and 
 linking the text subgroup to the one or more other text subgroups based on the similarity relationship. 
   
     
     
         13 . The method of  claim 12 , wherein determining text subgroups comprises determining text subgroups within the electronic text based on another similarity relationship of content within each text subgroup. 
     
     
         14 . The method of  claim 12 , wherein determining text subgroups comprises determining text subgroups based on one of chapters, paragraphs, and sentences of the electronic text. 
     
     
         15 . The method of  claim 12 , wherein linking the text subgroup to the one or more other text subgroups comprises storing a navigational aid in metadata of the electronic text that indicates association of the text subgroup with the one or more other text subgroups. 
     
     
         16 . The method of  claim 15 , further comprising presenting, for each text subgroup, a navigational link that links the text subgroup to the one or more other text subgroups. 
     
     
         17 . The method of  claim 12 , wherein determining the similarity relationship comprises determining a similarity relationship between the text subgroup and each other text subgroup positioned forward of the text subgroup within the electronic text, and
 wherein linking the text subgroup to one or more other text subgroups comprises linking the text subgroup to the other forward-positioned text subgroup having the highest similarity relationship.   
     
     
         18 . The method of  claim 12 , wherein determining the similarity relationship comprises determining a similarity relationship between the text subgroup and each other text subgroup positioned backward of the text subgroup within the electronic text,
 wherein linking the text subgroup to one or more other text subgroups comprises linking the text subgroup to the other backward-positioned text subgroup having the highest similarity relationship.   
     
     
         19 . The method of  claim 12 , wherein determining the similarity relationship comprises:
 using a semantic graph representing relations between words to compare words of the text subgroup and words in the one or more other text subgroups; and   using the comparison to link the text subgroup with the one or more other text subgroups.   
     
     
         20 . The method of  claim 19 , 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.