Techniques for personalized and adaptive search services

Abstract

Techniques are presented for automatically selecting information sources that are most relevant to user queries. Results of searches returned by information sources for queries are analyzed and the information sources are ranked based on this analysis. The information sources that have high rankings for a query are subsequently used to search for relevant results. This process can be adaptive, as the returned results of old queries can be analyzed at a later date to update the ranking of the information sources, automatic searches can be performed to update the ranking of the information sources, new queries can be used for analysis and stored, new information sources added, and old information sources deleted. A linguistic library is used to store personal categories for one or more users. and general categories. Each category is associated with keywords and ranked lists of information sources. The library also contains general categories, taxonomies, and dictionaries.

What is claimed is:  
     
         1 . A method, comprising: 
 sending a query to a plurality of information sources; and    ranking the information sources based on scores for results returned by the plurality of information sources.    
     
     
         2 . The method of  claim 1 , wherein the step of ranking further comprises the steps of: 
 receiving the results from each of the plurality of information sources; and    determining the scores for the results.    
     
     
         3 . The method of  claim 2 , wherein the query comprises at least one keyword.  
     
     
         4 . The method of  claim 3 , wherein the step of determining the scores farther comprises the steps of: 
 determining a quality measure for each keyword;    determining a quantity measure for each keyword; and    determining a score for each keyword based on the quality measure and the quantity measure.    
     
     
         5 . The method of  claim 4 , wherein the step of determining a quality measure further comprises the steps of: 
 determining how many times each keyword appears in each document accessible through the results from one of the information sources;    determining how many documents are accessible through the results from one of the information sources; and    dividing the number of times each keyword appears by the number of documents to determine the quality measure.    
     
     
         6 . The method of  claim 5 , wherein the step of the step of determining the scores for the results further comprises the steps of: 
 repeating the steps of determining a quality measure, determining a quantity measure, and determining a score for each keyword for each keyword and each information source; and    determining source scores for each source by adding the scores for each keyword.    
     
     
         7 . The method of  claim 6 , wherein the step of ranking the information sources further comprises the step of using the source scores to rank the information sources.  
     
     
         8 . The method of  claim 1 , further comprising the steps of: 
 storing the rankings for the information sources;    storing the query; and    performing the steps of sending a query and ranking the information sources for the stored query.    
     
     
         9 . The method of  claim 8 , wherein a user enters the query.  
     
     
         10 . The method of  claim 8 , wherein: 
 the step of storing the query further comprises the step of storing a plurality of queries;    the step of storing the rankings for the information sources further comprises the step of storing a set of rankings for each of the queries;    the method further comprises the step of selecting a query; and    the step of performing the steps of sending a query and ranking the information sources for the stored query further comprises the step of performing the steps of sending a query and ranking the information sources for the selected query.    
     
     
         11 . The method of  claim 1 , further comprising the steps of: 
 receiving a user request;    associating the user request with at least one keyword; and    creating the query from the at least one keyword.    
     
     
         12 . The method of  claim 11 , wherein the step of associating the user request further comprises the step of determining whether a word or words in the user request matches one or more descriptions, each description corresponding to a category.  
     
     
         13 . The method of  claim 12 , wherein the word or words in the user request do match with one or more descriptions and wherein the step of associating the user request further comprises the step of associating one or more keywords, corresponding to the category or categories having descriptions matching the one or more words, with the user request.  
     
     
         14 . The method of  claim 12 , wherein the word or words in the user request do not match with one or more descriptions and wherein the step of associating the user request further comprises the steps of: 
 using a dictionary to determine an additional word or additional words associated with the word or words; and    associating one or more keywords, corresponding to the category or categories having descriptions matching the one or more words, with the user request.    
     
     
         15 . The method of  claim 11 , further comprising the steps of: 
 providing the at least one keyword to the user.    
     
     
         16 . The method of  claim 11 , wherein the step of associating the user request further comprises the step of using a user specific taxonomy to associate the user request with the at least one keyword.  
     
     
         17 . The method of  claim 11 , wherein the user request comprises one or more of the followings: a description of a category and one or more words of a user query.  
     
     
         18 . An apparatus comprising: 
 one ore more memories that store computer-readable code; and    one or more processors operatively coupled to the one or more memories, the one or more processors configured to implement the computer-readable code, the computer-readable code configured to: 
 send a query to a plurality of information sources; and  
 rank the information sources based on scores for results returned by the plurality of information sources.  
   
     
     
         19 . An article of manufacture comprising: 
 a computer-readable medium having computer-readable code means embodied thereon, said computer-readable program code means comprising: 
 a step to send a query to a plurality of information sources; and  
 a step to rank the information sources based on scores for results returned by the plurality of information sources.