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Search shortcuts using click-through data

Published: 09 February 2009 Publication History

Abstract

Major Web Search Engines take as a common practice to provide Suggestions to users in order to enhance their search experience. Such suggestions have normally the form of queries that are, to some extent, "similar" to the queries already submitted by the same or related users. The final aim of query suggestions is typically to help users to satisfy their information needs more quickly. In this paper we face this problem from a somewhat different perspective, and we propose a new query suggestion model based on Search Shortcuts, that consist in finding and proposing to the user "Successful" queries that allowed, in the past, several users to satisfy their information needs. This model differs from traditional query suggestion approaches, and allows the evaluation to be performed effectively by exploiting actual user sessions from the Microsoft 2006 RFP dataset. We evaluate several algorithms applied to this problem, both traditional Collaborative Filtering techniques and ad-hoc solutions, and report on preliminary results achieved.

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    cover image ACM Conferences
    WSCD '09: Proceedings of the 2009 workshop on Web Search Click Data
    February 2009
    95 pages
    ISBN:9781605584348
    DOI:10.1145/1507509
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 09 February 2009

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    1. evaluation
    2. model
    3. search shortcut

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