13. A computer-implemented method of identifying and clustering queries that are increasing in popularity using a computing system having memory, processor, and data storage subsystems, the computer-implemented method comprising: receiving a search query request from a user input device; identifying a spike in incoming query stream activity comprising the search query request; temporally correlating the spike in the incoming query stream activity with relevant content from a plurality of historical indices as a result of searching said historical indices; correlating the spike in the incoming query stream activity with relevant content from a plurality of fresh indices as a result of searching said fresh indices, wherein the fresh indices contain information and results from recently crawled content sources; analyzing results from searching the historical indices and the fresh indices to determine if the search query request should be clustered with an existing group of search query results; prioritizing results of the search query request according to an age and size of identified cyclic clustered results; and communicating the prioritized results of the search query request to a user output device.
13. A computer-implemented method of identifying and clustering queries that are increasing in popularity using a computing system having memory, processor, and data storage subsystems, the computer-implemented method comprising: receiving a search query request from a user input device; identifying a spike in incoming query stream activity comprising the search query request; temporally correlating the spike in the incoming query stream activity with relevant content from a plurality of historical indices as a result of searching said historical indices; correlating the spike in the incoming query stream activity with relevant content from a plurality of fresh indices as a result of searching said fresh indices, wherein the fresh indices contain information and results from recently crawled content sources; analyzing results from searching the historical indices and the fresh indices to determine if the search query request should be clustered with an existing group of search query results; prioritizing results of the search query request according to an age and size of identified cyclic clustered results; and communicating the prioritized results of the search query request to a user output device. 16. The computer-implemented method of claim 13 , further comprising suggesting temporally relevant online advertisements to the user device.