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Do we mean the same?: disambiguation of extracted keyword queries for database search

Published: 28 June 2009 Publication History

Abstract

Users often try to accumulate information on a topic of interest from multiple information sources. In this case a user's informational need might be expressed in terms of an available relevant document, e.g. a web-page or an e-mail attachment, rather than a query. Database search engines are mostly adapted to the queries manually created by the users. In case a user's informational need is expressed in terms of a document, we need algorithms that map keyword queries automatically extracted from this document to the database content.
In this paper we analyze the impact of selected document and database statistics on the effectiveness of keyword disambiguation for manually created as well as automatically extracted keyword queries. Our evaluation is performed using a set of user queries from the AOL query log and a set of queries automatically extracted from Wikipedia articles both executed against the Internet Movie Database (IMDB). Our experimental results show that (1) knowledge of the document context is crucial in order to extract meaningful keyword queries; (2) statistics which enable effective disambiguation of user queries are not sufficient to achieve the same quality for the automatically extracted requests.

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Cited By

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  • (2019)Disambiguation and Result Expansion in Keyword Search Over Relational Databases2019 IEEE 35th International Conference on Data Engineering (ICDE)10.1109/ICDE.2019.00248(2101-2105)Online publication date: Apr-2019
  • (2012)SODAProceedings of the VLDB Endowment10.14778/2336664.23366675:10(932-943)Online publication date: 1-Jun-2012
  • (2010)Multi-dimensional keyword-based image annotation and searchProceedings of the 2nd International Workshop on Keyword Search on Structured Data10.1145/1868366.1868371(1-6)Online publication date: 6-Jun-2010

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  1. Do we mean the same?: disambiguation of extracted keyword queries for database search

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    cover image ACM Conferences
    KEYS '09: Proceedings of the First International Workshop on Keyword Search on Structured Data
    June 2009
    54 pages
    ISBN:9781605585703
    DOI:10.1145/1557670
    • General Chair:
    • M. Tamer Özsu,
    • Program Chairs:
    • Yi Chen,
    • Lei Chen
    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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    Publication History

    Published: 28 June 2009

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    Author Tags

    1. extracted keyword queries
    2. keyword disambiguation

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    • (2019)Disambiguation and Result Expansion in Keyword Search Over Relational Databases2019 IEEE 35th International Conference on Data Engineering (ICDE)10.1109/ICDE.2019.00248(2101-2105)Online publication date: Apr-2019
    • (2012)SODAProceedings of the VLDB Endowment10.14778/2336664.23366675:10(932-943)Online publication date: 1-Jun-2012
    • (2010)Multi-dimensional keyword-based image annotation and searchProceedings of the 2nd International Workshop on Keyword Search on Structured Data10.1145/1868366.1868371(1-6)Online publication date: 6-Jun-2010

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