Systems and Methods for Enhancing Web-Based Searching

Abstract

A system for enhancing web-based searching is provided. Categorizing and clustering techniques are used to optimize searching. Businesses are classified using a control group of predetermined categories. The predetermined categories may be SIC codes or headings that are used to describe business activities. The website addresses for a business listed in the control group is determined, and the content of the business's website is extracted. The extracted content is associated with the predetermined category that the business is classified under. The extracted content is used to further enhance the overall classification scheme. The system may compare and match the extracted content with content of other business' websites, which are similarly categorized. If a relevant keyword match is identified in several of the websites, the keyword may be used to update the classification scheme. A new category or sub-category can be created based on this keyword. Furthermore, when a search is performed, the search results are organized by these categories, and using various processes, the most common results are kept and the less relevant results are discarded.

1 . A computer implemented system for optimizing searching comprising:
 one or more computer processors executing a search query;   a search engine responsive to the search query;   a clustering engine, in communication with the search engine, processing search result hits resulting from the query, where the clustering engine clusters the hits using an SIC classification of business activities; and   the clustering engine grouping the hits according to their respective SIC code using at least the first two digits of the SIC code to group hits and eliminate false positives.   
   
   
       2 . A computer implemented system for optimizing searching as in  claim 1  wherein the SIC predefined taxonomy of SIC business activities are not computer generated. 
   
   
       3 . A computer implemented system as in  claim 1  wherein each of the business activities in the SIC predefined taxonomy corresponds to a business descriptor. 
   
   
       4 . A computer implemented system as in  claim 1  wherein the search engine responds to the search query by conducting a full-text index search of website content; and
 the clustering engine grouping the hits according to their respective SIC code by clustering results that are responsive to the full-text index search, where the full-text index search results are clustered based on associated SIC codes.   
   
   
       5 . A computer implemented system as in  claim 4  wherein at least a portion of the full-text index search results are clustered by:
 matching SIC codes associated with the full-text indexed search results; and   grouping the full-text index search results having matching SIC codes.   
   
   
       6 . A computer implemented system in  claim 5  wherein grouping the full-text index search results having matching SIC codes further includes:
 determining a group hit count for each group;   determining if the group hit count is above a threshold value;   displaying groups of hits that are above the threshold value, where each of the displayed groups of hits are displayed with a heading corresponding to their respective SIC code and with counts showing the number of hits in the group, where the SIC code heading displayed is an associated SIC business descriptor.   
   
   
       7 . A computer implemented system in  claim 6  further includes responding to a selection of one of the SIC code headings displayed by presenting hits in the group corresponding to the selected SIC code heading. 
   
   
       8 . A computer implemented system in  claim 5  wherein grouping full-text index search results having matching SIC codes further includes using the first three digits of the SIC codes to group the full-text index search results. 
   
   
       9 . A computer implemented system in  claim 8  wherein if the full-text index search results fail to include one or more groups of hits having a count above a threshold value, using the first two digits of the SIC codes to group hits.