Method and apparatus for concept-based visual

Abstract

A method and apparatus is provided for visually coding or sorting search results based on the similarity of the search results to one or more concepts. A search query containing search terms is used to conduct a web search and obtain search results comprising a number of document surrogates describing the located web pages. Concepts are obtained using the search terms and the similarities between the obtained concepts and the search results are evaluated. The search results are then displayed in a manner that indicates the relative similarity of search results to one or more of the determined concepts, such as by sorting the search results based on the level of similarity of the search results to one or more concepts or by providing an accordance indicator with each displayed search result the accordance indicators indicating the similarity of the corresponding search result with one ore more of the concepts.

Description

RELATED APPLICATION[0001]The present application claims the benefit of Canadian Patent Application Serial No. 2,549,536 filed Jun. 6, 2006, which is incorporated herein in its entirety by reference.BACKGROUND[0002]The World Wide Web has given computer users on the Internet access to vast amounts of information in the form of billions of Web pages. Each of these pages can be accessed directly by a user typing the URL (universal resource locator) of a web page into a web browser on the user's computer, but often, a person is more likely to access a website by finding it with the use of search engine. A search engine allows a user to input a search query made up of words or terms that a user thinks will be used in the web pages containing the information he or she is looking for. The search engine will attempt to match web pages to the terms in the search query and will then return the located web pages to the user.[0003]The search results generated from a user's query typically consis...

AI Technical Summary

Problems solved by technology

However, while it is clear that significant effort has gone into creating web search engines that can index billion of documents and return the search results in a fraction of a second, this has resulted in the creation of the problem of search queries returning numerous results.

While relevant documents might be present in the search results returned from a search engine, often the returned search results consist of tens or hundreds of individual documents making it hard for a user to determine which of the search results may or may not be relevant to the information the user is looking for.

Although this list-based representation makes it easy to evaluate a single document, it does not support the users in the broader tasks of manipulating the search results, comparing documents, or finding a set of relevant documents.

If hundreds of documents are returned it is inefficient if not completely impractical to have a user review hundreds of results to determine the most relevant document located in the search.

One solution that can be used to address these numerous search results is for the user to reformulate his or her search query to narrow the search with the result that fewer document are located mating the search query, however, in many cases there may be high quality relevant documents buried in the search results set that were missed because the users did not look at enough search result pages.

One of the problems with these systems is that determining what the clusters should be centered around and determining an adequate description of the cluster.

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