Generating descriptions of matching resources based on the kind, quality, and relevance of the available sources of information about the matching resources

Abstract

Techniques are provided for generating descriptions of matching resources in a manner that takes into account the kind, quality, and relevance of the available sources of information about the matching resources. For example, after the search engine identifies matching resources based on the query terms, the search engine determines the kinds of available sources of information about each matching resource. For each matching resource, based on the kinds of available sources of information about the matching resource, one of a plurality of processes is selected to generate a description for the matching resource. Using the content-sensitive description generation techniques described herein, a single result set may include abstracts that were generated using several different processes, where the difference in process corresponds to a difference in the kind, quality, and relevance of the available sources of information about each matching resource.

What is claimed is: 
     
         1 . A computer system comprising:
 a memory storing instructions;   one or more processors coupled to the memory, wherein the one or more processors execute the instructions, which causes the one or more processors to:
 identify one or more sections in a document, wherein each section of the one or more sections comprises one or more text strings; 
 identify one or more selectable links in a particular section of the one or more sections in the document; 
 assign a weight to each section of the one or more sections, wherein the weight assigned to the particular section is based, at least in part, on a portion of the particular section that includes the one or more selectable links; 
 generate a summary of the document based, at least in part, on the weight assigned to each section of the one or more sections. 
   
     
     
         2 . The computer system of  claim 1 , wherein:
 the instructions further cause the one or more processors to determine, for the particular section of the one or more sections in the document, a number of characters within the particular section that are not contained in a selectable link;   the weight assigned to the particular section is based, at least in part, on the number of characters.   
     
     
         3 . The computer system of  claim 1 , wherein:
 the instructions further cause the one or more processors to determine, for the particular section of the one or more sections in the document, a percentage of characters within the particular section that are not contained in a selectable link;   the weight assigned to the particular section is based, at least in part, on the percentage of characters.   
     
     
         4 . The computer system of  claim 1 , wherein the instructions further cause the one or more processors to extract the one or more sections in the document based, at least in part, on one or more specified fields in the document. 
     
     
         5 . The computer system of  claim 1 , wherein the instructions further cause the one or more processors to:
 find a plurality of text strings within a document, wherein each text string of the plurality of text strings corresponds to at least one section of one or more sections in the document;   associate, for each text string in the plurality of text strings, a score that is based at least in part on the weight that is associated with the section that corresponds to the text string;   select one or more text strings, from the plurality of text strings, for generating a summary of the document based, at least in part, on the score associated with each text string of the plurality of text strings;   wherein generating the summary of the document is based, at least in part, on the one or more text strings that were selected.   
     
     
         6 . The computer system of  claim 5 , wherein, for each text string in the plurality of text strings:
 the instructions further cause the one or more processors to determine a number of words in the text string; and   associating the score for the text string is based, at least in part, on the number of words in the text string.   
     
     
         7 . The computer system of  claim 5 , wherein selecting the one or more text strings, from the plurality of text strings, comprises comparing the score associated with the text string to a particular threshold. 
     
     
         8 . A method comprising:
 identifying one or more sections in a document, wherein each section of the one or more sections comprises one or more text strings;   identifying one or more selectable links in a particular section of the one or more sections in the document;   assigning a weight to each section of the one or more sections, wherein the weight assigned to the particular section is based, at least in part, on a portion of the particular section that includes the one or more selectable links;   generating a summary of the document based, at least in part, on the weight assigned to each section of the one or more sections;   wherein the method is performed by one or more processors.   
     
     
         9 . The method of  claim 8  further comprising:
 determining, for the particular section of the one or more sections in the document, a number of characters within the particular section that are not contained in a selectable link; 
 wherein the weight assigned to the particular section is based, at least in part, on the number of characters. 
 
     
     
         10 . The method of  claim 8  further comprising:
 determining, for the particular section of the one or more sections in the document, a percentage of characters within the particular section that are not contained in a selectable link; 
 wherein the weight assigned to the particular section is based, at least in part, on the percentage of characters. 
 
     
     
         11 . The method of  claim 8  further comprising extracting the one or more sections in the document based, at least in part, on one or more specified fields in the document. 
     
     
         12 . The method of  claim 8  further comprising:
 finding a plurality of text strings within a document, wherein each text string of the plurality of text strings corresponds to at least one section of one or more sections in the document; 
 associating, for each text string in the plurality of text strings, a score that is based at least in part on the weight that is associated with the section that corresponds to the text string; 
 selecting one or more text strings, from the plurality of text strings, for generating a summary of the document based, at least in part, on the score associated with each text string of the plurality of text strings; 
 wherein generating the summary of the document is based, at least in part, on the one or more text strings that were selected. 
 
     
     
         13 . The method of  claim 12  further comprising, for each text string in the plurality of text strings:
 determining a number of words in the text string; 
 wherein associating the score for the text string is based, at least in part, on the number of words in the text string. 
 
     
     
         14 . The method of  claim 12 , wherein selecting the one or more text strings, from the plurality of text strings, comprises comparing the score associated with the text string to a particular threshold. 
     
     
         15 . A computer system comprising:
 one or more processors;   a memory;   a module capable of identifying one or more sections in a document, wherein each section of the one or more sections comprises one or more text strings;   a module capable of identifying one or more selectable links in a particular section of the one or more sections in the document;   a module capable of assigning a weight to each section of the one or more sections, wherein the weight assigned to the particular section is based, at least in part, on a portion of the particular section that includes the one or more selectable links;   a module capable of generating a summary of the document based, at least in part, on the weight assigned to each section of the one or more sections.   
     
     
         16 . The computer system of  claim 15  further comprising:
 a module capable of determining, for the particular section of the one or more sections in the document, a number of characters within the particular section that are not contained in a selectable link; 
 wherein the weight assigned to the particular section is based, at least in part, on the number of characters. 
 
     
     
         17 . The computer system of  claim 15  further comprising:
 a module capable of determining, for the particular section of the one or more sections in the document, a percentage of characters within the particular section that are not contained in a selectable link; 
 wherein the weight assigned to the particular section is based, at least in part, on the percentage of characters. 
 
     
     
         18 . The computer system of  claim 15  further comprising a module capable of extracting the one or more sections in the document based, at least in part, on one or more specified fields in the document. 
     
     
         19 . The computer system of  claim 15  further comprising:
 a module capable of finding a plurality of text strings within a document, wherein each text string of the plurality of text strings corresponds to at least one section of one or more sections in the document; 
 a module capable of associating, for each text string in the plurality of text strings, a score that is based at least in part on the weight that is associated with the section that corresponds to the text string; 
 a module capable of selecting one or more text strings, from the plurality of text strings, for generating a summary of the document based, at least in part, on the score associated with each text string of the plurality of text strings; 
 wherein generating the summary of the document is based, at least in part, on the one or more text strings that were selected. 
 
     
     
         20 . The computer system of  claim 19  further comprising, for each text string in the plurality of text strings:
 a module capable of determining a number of words in the text string; 
 wherein associating the score for the text string is based, at least in part, on the number of words in the text string. 
 
     
     
         21 . The computer system of  claim 19 , wherein selecting the one or more text strings, from the plurality of text strings, comprises comparing the score associated with the text string to a particular threshold.