Web browser accessible search engine that identifies search result maxima through user search flow and result content comparison
A search server searches web sites based upon a search string. Maxima categories are provided that sort search results based upon popularity and/or context similarity. A web browser displays the search result pages. A maxima determination module within the search server responds to the delivery of the initial search string by first categorizing search results applicability to the search string on the basis of maxima or by generating maxima categories with search results that correlated to the search string. Search results within each applicable maximum are then sorting on the basis of popularity within each of the maxima categories to effectuate popularity ranks for each search result or web page. User interaction with search results are monitored to better select search maxima and popularity ranks for subsequent search result requests for this search string, whereby the desirability of search results provided to the user improves over time.
1. A computing device comprising:
a communication interface;
a memory; and
a processing circuitry coupled to the communication interface and to the memory, the processing circuitry, memory, and communication interface configured to:
receive a search request from a user device, the search request including a search string;
determine first search results using the search request, the search results selected from a first maxima category and a second maxima category within a plurality of maxima categories of searchable data organized based on content similarity and relative popularity, wherein of the first and second maxima categories contains hierarchically ordered sub-maxima categories that further organize the searchable data within the maxima categories based on content similarity;
deliver the first search results to the user device;
receive user interaction data from the user device indicating user interaction within the first maxima category and the second maxima category;
process the user interaction data to identify second search results selected from a first sub-maxima category and a second sub-maxima category of the first maxima category; and
deliver the second search results to the user device.
2. The computing device of claim 1 , wherein the user interaction data comprises answers to a pop-up window questionnaire.
3. The computing device of claim 1 , wherein the user interaction data comprises greater interaction with the first maxima category than interaction with the second maxima category.
4. The computing device of claim 1 , wherein the processing circuitry is further configured to:
allocate a first portion of the search results to a first type of content; and
allocate a second portion of the search results to a second type of content.
5. The computing device of claim 1 , wherein the processing circuitry is further configured to select content of the plurality of maxima categories based on user interaction data collected from search support modules installed on a plurality of user devices.
6. The computing device of claim 1 , wherein content of the plurality of maxima categories changes over time as a plurality of users interact with search results.
7. The computing device of claim 1 , wherein the user interaction data is based upon numbers of respective interaction with the first and second maxima categories.
8. The computing device of claim 1 , wherein the processing circuitry is further configured to select the first and second maxima categories from the plurality of maxima categories based on popularity of the first and second maxima categories.
9. The computing device of claim 1 , wherein the processing circuitry is further configured to indicate an association between at least one of the first and second maxima groups with particular search results to the user device.
10. The computing device of claim 1 , wherein the processing circuitry is further configured to iteratively process user interaction data to select other search results from determined interesting maxima categories and to eliminate search results from determined uninteresting maxima categories over time.
11. A method of operating a computing device comprising:
receiving a search request from a user device, the search request including a search string;
determining first search results using the search request, the search results selected from a first maxima category and a second maxima category within a plurality of maxima categories of searchable data organized based on content similarity and relative popularity, wherein of the first and second maxima categories contains hierarchically ordered sub-maxima categories that further organize the searchable data within the maxima categories based on content similarity;
delivering the first search results to the user device;
receiving user interaction data from the user device indicating user interaction within the first maxima category and the second maxima category;
processing the user interaction data to identify second search results selected from a first sub-maxima category and a second sub-maxima category of the first maxima category; and
delivering the second search results to the user device.
12. The method of claim 11 , wherein the user interaction data comprises answers to a pop-up window questionnaire.
13. The method of claim 11 , wherein the user interaction data comprises greater interaction with the first maxima category than interaction with the second maxima category.
14. The method of claim 11 , further comprising:
allocating a first portion of the search results to a first type of content; and
allocating a second portion of the search results to a second type of content.
15. The method of claim 11 , further comprising selecting content of the plurality of maxima categories based on user interaction data collected from search support modules installed on a plurality of user devices.
16. The method of claim 11 , wherein content of the plurality of maxima categories changes over time as a plurality of users interact with search results.
17. The method of claim 11 , wherein the user interaction data is based upon respective interaction with the first and second maxima categories.
18. The method of claim 11 , further comprising selecting the first and second maxima categories from the plurality of maxima categories based on popularity of the first and second maxima categories.
19. The method of claim 11 , further comprising indicating an association between at least one of the first and second maxima groups with particular search results to the user device.
20. The method of claim 11 , further comprising iteratively processing user interaction data to select other search results from determined interesting maxima categories and to eliminate search results from determined uninteresting maxima categories over time.