IDENTIFYING RELEVANT INFORMATION SOURCES FROM USER ACTIVITY
First Claim
1. A computer-implemented process for finding relevant sources of information for a search query, comprising:
- constructing a weighted model that associates every term in multiple search queries with relevant sources from multiple users'"'"' searching and browsing activity;
inputting a new query that is represented as a set of terms;
determining relevant sources for all terms in the new query using the weighted model to determine an overall prediction of the most relevant sources for the query; and
displaying the determined relevant sources for the new query.
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Accused Products
Abstract
A relevant information source identification technique that exploits a combination of searching and browsing activity of many users to identify relevant resources for future queries. The technique relies on such data to identify relevant information sources for new queries. In one embodiment, the technique is term-based: past queries are decomposed into individual (possibly overlapping) terms and phrases, and the most relevant documents are identified for each phrase from the browsing patterns of users that follow the query. Then, for a new query that consists of several terms or phrases, the most relevant destinations for each term/phrase are combined to produce overall predictions of the best or most relevant sources for the new query. This allows for providing predictions for previously unseen queries, which comprise a large proportion of the overall query volume.
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Citations
20 Claims
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1. A computer-implemented process for finding relevant sources of information for a search query, comprising:
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constructing a weighted model that associates every term in multiple search queries with relevant sources from multiple users'"'"' searching and browsing activity; inputting a new query that is represented as a set of terms; determining relevant sources for all terms in the new query using the weighted model to determine an overall prediction of the most relevant sources for the query; and displaying the determined relevant sources for the new query. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-implemented process for finding relevant sources of information for a search query on a network, comprising:
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inputting a set of queries and associated search trails from several users; creating a weighted model that associates every term or phrase in each search query with relevant sources from the several users'"'"' search trails; inputting a new query comprising a set of terms; determining probability of relevant sources for each search trail for each term in the new query using the weighted model; and determining the overall relevance of each source document for the entire new query by combining the probability of relevant sources for each term. - View Dependent Claims (12, 13, 14, 15)
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16. A system for finding relevant sources of information on a network in response to a search query, comprising:
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a general purpose computing device; a computer program comprising program modules executable by the general purpose computing device, wherein the computing device is directed by the program modules of the computer program to, receive a set of users'"'"' search queries and associated search result histories; create search trails that each include a query, a sequence of URLs accessed by a user including the time spent on each URL and tokenizations of the search query terms; create a weighted model that associates every term in a query with one or more relevant sources based on users'"'"' searching and browsing history; input a new search query, broken into terms; use the weighted model to rank the relevance of sources by predicting the most relevant sources for each of the terms of the new query; output the most relevant sources for the new search query. - View Dependent Claims (17, 18, 19, 20)
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Specification