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Inferring the most important types of a query: a semantic approach

Published: 20 July 2008 Publication History

Abstract

In this paper we present a technique for ranking the most important types or categories for a given query. Rather than trying to find the category of the query, known as query categorization, our approach seeks to find the most important types related to the query results. Not necessarily the query category falls into this ranking of types and therefore our approach can be complementary.

References

[1]
A. P. de Vries, J. A. Thom, A. M. Vercoustre, N. Craswell, and M. Lalmas. Inex 2007 entity ranking track guidelines. In INEX 2007 Workshop preproceedings, pages 481--486, 2007.
[2]
M. Tvarozek and M. Bielikova. Adaptive faceted browser for navigation in open information spaces. In WWW '07, pages 1311--1312, New York, NY, USA, 2007. ACM.
[3]
H. Zaragoza, H. Rode, P. Mika, J. Atserias, M. Ciaramita, and G. Attardi. Ranking very many typed entities on wikipedia. In CIKM '07, pages 1015--1018, New York, NY, USA, 2007. ACM.

Cited By

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  • (2024)Extreme Classification for Answer Type Prediction in Question AnsweringProceedings of the 2023 ACM/IEEE Joint Conference on Digital Libraries10.1109/JCDL57899.2023.00041(232-236)Online publication date: 26-Jun-2024
  • (2022)Fine-Grained Entity Typing with a Type Taxonomy: a Systematic ReviewIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3148980(1-1)Online publication date: 2022
  • (2018)Understanding Information NeedsEntity-Oriented Search10.1007/978-3-319-93935-3_7(225-267)Online publication date: 3-Oct-2018
  • Show More Cited By

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  1. Inferring the most important types of a query: a semantic approach

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    cover image ACM Conferences
    SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
    July 2008
    934 pages
    ISBN:9781605581644
    DOI:10.1145/1390334
    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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    New York, NY, United States

    Publication History

    Published: 20 July 2008

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    Author Tags

    1. entity ranking
    2. faceted search
    3. type ranking

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    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    View all
    • (2024)Extreme Classification for Answer Type Prediction in Question AnsweringProceedings of the 2023 ACM/IEEE Joint Conference on Digital Libraries10.1109/JCDL57899.2023.00041(232-236)Online publication date: 26-Jun-2024
    • (2022)Fine-Grained Entity Typing with a Type Taxonomy: a Systematic ReviewIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3148980(1-1)Online publication date: 2022
    • (2018)Understanding Information NeedsEntity-Oriented Search10.1007/978-3-319-93935-3_7(225-267)Online publication date: 3-Oct-2018
    • (2018)Entity RetrievalEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_80724(1326-1331)Online publication date: 7-Dec-2018
    • (2017)On Type-Aware Entity RetrievalProceedings of the ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3121050.3121054(27-34)Online publication date: 1-Oct-2017
    • (2017)Target Type Identification for Entity-Bearing QueriesProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080659(845-848)Online publication date: 7-Aug-2017
    • (2017)Entity RetrievalEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_80724-1(1-6)Online publication date: 28-Aug-2017
    • (2016)Contextualized ranking of entity types based on knowledge graphsWeb Semantics: Science, Services and Agents on the World Wide Web10.5555/2938782.293886437:C(170-183)Online publication date: 1-Mar-2016
    • (2016)Exemplar queriesThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-016-0429-225:6(741-765)Online publication date: 1-Dec-2016
    • (2014)Exemplar queriesProceedings of the VLDB Endowment10.14778/2732269.27322737:5(365-376)Online publication date: 1-Jan-2014
    • Show More Cited By

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