Abstract: A system analyzes data from a search engine. A User Search Bundler analyzes User Searches groups similar User Searches into User Search Bundles, and an Intent Processor produces Intents based on the User Search Bundles. A Factor Generator considers User Searches and related information to produce Factors, where each Factor is with regard to a particular Result from a set of Search Results. A Relevance Classifier receives the Factors and operates based thereon to produce a Judgment for each Result. A Metric Generator produces Metrics based on the Factors and the Judgments, and, a data synthesizer formats extracted data into databases.

Abstract: A method is provided for analyzing a plurality of search sessions to identify intent-based clusters therein. Each session comprises at least one received query from a user and a corresponding set of returned search results, and each set of search results includes or refers to at least one piece of content. Each cluster represents a group of similar search sessions that are perceived as representing a common purpose and that can be mapped to a common set of search results. In the method, for each search session, each received query thereof, the corresponding set of search results, and whether any particular piece of content of the search results was acceptable to the user as responsive to the corresponding search session are identified. Thereafter, search sessions are grouped into clusters.