Learning Synonymous Object Names from Anchor Texts

Abstract

A repository contains objects representing entities. The objects also include facts about the represented entities. The facts are derived from source documents. A synonymous name of an object is determined by identifying a source document from which one or more facts of the entity represented by the object were derived, identifying a plurality of linking documents that link to the source document through hyperlinks, each hyperlink having an anchor text, processing the anchor texts in the plurality of linking documents to generate a collection of synonym candidates for the entity represented by the object, and selecting a synonymous name for the entity represented by the object from the collection of synonym candidates.

What is claimed is: 
     
         1 . A method of determining a synonymous name for an entity comprising:
 at a computer system having one or more processors and memory storing one or more programs configured for execution by the one or more processors:
 identifying a source document from which one or more facts of an entity were derived; 
 identifying a plurality of linking documents having hyperlinks to the source document, each hyperlink having an anchor text; 
 generating a collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents; 
 selecting a synonymous name for the entity from the collection of synonym candidates; and 
 storing the synonymous name in association with the entity. 
   
     
     
         2 . The method of  claim 1 , wherein identifying the source document further comprises:
 identifying a list of source documents from which one or more facts of the entity were derived;   removing from the list identifiers of source documents from which one or more facts of another entity were derived from the list; and   identifying the source document from the list of source documents.   
     
     
         3 . The method of  claim 1 , wherein generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprises:
 normalizing the anchor texts in the plurality of linking documents; and   generating the collection of synonym candidates for the entity using the normalized anchor texts.   
     
     
         4 . The method of  claim 3 , wherein normalizing the anchor texts in the plurality of linking documents further comprises:
 identifying a language of one of the plurality of linking documents; and   applying normalization rules for the language to normalize the anchor text in the one of the plurality of linking documents.   
     
     
         5 . The method of  claim 1 , wherein generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprises:
 extracting a noun phrase from one of the anchor texts in the plurality of linking documents; and   generating the collection of synonym candidates for the entity using the extracted noun phrase.   
     
     
         6 . The method of  claim 1 , wherein generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprises:
 removing a prefix or a suffix from the anchor texts in the plurality of linking documents.   
     
     
         7 . The method of  claim 1 , wherein generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprises:
 matching an anchor text with a black list of texts; and   responsive to detecting a match of the anchor text with the black list, removing the anchor text from the collection of synonym candidates for the entity.   
     
     
         8 . The method of  claim 1 , wherein generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprises:
 matching an anchor text with a white list of texts; and   responsive to detecting a match of the anchor text with the white list, adding the anchor text into the collection of synonym candidates for the entity.   
     
     
         9 . The method of  claim 1 , wherein selecting the synonymous name for the entity from the collection of synonym candidates further comprises:
 selecting a synonym candidate occurring at a frequency in the collection of synonym candidates no less than a minimum threshold as the synonymous name for the entity.   
     
     
         10 . The method of  claim 9 , further comprising:
 responsive to a synonym candidate occurring at a frequency in the collection of synonym candidates less than the minimum threshold, adding the synonym candidate into a black list of texts.   
     
     
         11 . The method of  claim 1 , wherein selecting the synonymous name for the entity from the collection of synonym candidates further comprises:
 selecting a synonym candidates occurring at a frequency in the collection of synonym candidates no more than a maximum threshold as the synonymous name for the entity.   
     
     
         12 . The method of  claim 11 , further comprising:
 responsive to a synonym candidate occurring at a frequency in the collection of synonym candidates more than the maximum threshold, adding the synonym candidate into a black list of texts.   
     
     
         13 . The method of  claim 1 , wherein selecting the synonymous name for the entity from the collection of synonym candidates further comprises:
 determining quality for the plurality of linking documents; and   selecting the synonymous name for the entity from the collection of synonym candidates based on the quality of the linking document having the anchor text from which the synonymous name was generated.   
     
     
         14 . A system, for determining a synonymous name for an entity, comprising:
 one or more processors; and   memory storing one or more programs to be executed by the one or more processors;   the one or more programs comprising instructions for:
 identifying a source document from which one or more facts of an entity were derived; 
 identifying a plurality of linking documents having hyperlinks to the source document, each hyperlink having an anchor text; 
 generating a collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents; 
 selecting a synonymous name for the entity from the collection of synonym candidates; and 
 storing the synonymous name in association with the entity. 
   
     
     
         15 . The system of  claim 14 , wherein the instructions for identifying a source document further comprises:
 instructions for identifying a list of source documents from which one or more facts of the entity were derived;   instructions for removing from the list identifiers of source documents from which one or more facts of another entity were derived from the list; and   instructions for identifying the source document from the list of source documents.   
     
     
         16 . The system of  claim 14 , wherein the instructions for generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further comprise:
 instructions for normalizing the anchor texts in the plurality of linking documents; and   instructions for generating the collection of synonym candidates for the entity using the normalized anchor texts.   
     
     
         17 . The system of  claim 14 , wherein the instructions for selecting the synonymous name for the entity from the collection of synonym candidates further comprises instructions for:
 determining quality for the plurality of linking documents; and   selecting the synonymous name for the entity from the collection of synonym candidates based on the quality of the linking document having the anchor text from which the synonymous name was generated.   
     
     
         18 . A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for:
 identifying a source document from which one or more facts of an entity were derived;   identifying a plurality of linking documents having hyperlinks to the source document, each hyperlink having an anchor text;   generating a collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents;   selecting a synonymous name for the entity from the collection of synonym candidates; and   storing the synonymous name in association with the entity.   
     
     
         19 . The non-transitory computer readable storage medium of  claim 18 , wherein the instructions for identifying a source document further includes instructions for:
 identifying a list of source documents from which one or more facts of the entity were derived;   removing from the list identifiers of source documents from which one or more facts of another entity were derived from the list; and   identifying the source document from the list of source documents.   
     
     
         20 . The non-transitory computer readable storage medium of  claim 18 , wherein the instructions for generating the collection of synonym candidates for the entity in accordance with the anchor texts in the plurality of linking documents further includes instructions for:
 normalizing the anchor texts in the plurality of linking documents; and   generating the collection of synonym candidates for the entity using the normalized anchor texts.