WWW2009 EPrints

A Probabilistic Model Based Approach for Blended Search

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Abstract

In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this model are learned from search engine query log through unigram language model. Our experimental exploration shows that, (1) a large number of queries in generic Web search have vertical search intentions; and (2) our proposed algorithm can effectively blend vertical search results into generic Web search, which can improve the Mean Average Precision (MAP) by as much as 16% compared to traditional Web search without blending. these components into a single list. However, from the classical meta-search problem’s configuration, the query log of component search engines is not available for study. In this extended abstract, we model the blended search problem based on the conditional dependencies among queries, VSEs and all the search results. We utilize the usage information, i.e. query log, of all the VSEs, which are not available for traditional metasearch engines, to learn the model parameters by the smoothed unigram language model. Finally, given a user query, the search results from both generic Web search and different VSEs are ranked together by inferring their probabilities of relevance to the given query. The main contributions of this work are, (1) through studying the belonging vertical search engines’ query log of a commercial search engine, we show the importance of blended search problem; (2) we propose a novel probabilistic model based approach to explore the blended search problem; and (3) we experimentally verify that our proposed algorithm can effectively blend vertical search results into generic Web search, which can improve the MAP as much as 16% in contrast to traditional Web search without vertical search blending and 10% to some other some ranking baseline.

Fun web stuff for this record

RKBExplorer (from linked data workshop)
URI: http://eprints.rkbexplorer.com/id/www2009/eprints-118
Browse the data for this paper at RKBExplorer
REST Interface
http://www2009.eprints.org/cgi/rest/eprint/118/
ORE Resource Map
ORE was described in the Linked Data Workshop. View Resource Map
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About this site

This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.

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We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it...

Fun Stuff

OAI:
WWW2009 EPrints supports OAI 2.0 with a base URL of http://www2009.eprints.org/cgi/oai2
JSON
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Feel free to contact me (Christopher Gutteridge) with any other queries or suggestions. ...Or if you do something cool with the data which we should link to!

Handy Tools

These are not directly related to the EPrints set up, but may be of use to delegates.

Social tool links
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SplashURL.net
When demoing live websites, use this tool to shorten the current URL and make it appaer real big, your audience can then easily type in the short URL and get to the same page as you. Available as a javascript bookmark