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Interactive retrieval based on faceted feedback

Published: 19 July 2010 Publication History

Abstract

Motivated by the commonly used faceted search interface in e-commerce, this paper investigates interactive relevance feedback mechanism based on faceted document metadata. In this mechanism, the system recommends a group of document facet-value pairs, and lets users select relevant ones to restrict the returned documents. We propose four facet-value pair recommendation approaches and two retrieval models that incorporate user feedback on document facets. Evaluated based on user feedback collected through Amazon Mechanical Turk, our experimental results show that the Boolean filtering approach, which is widely used in faceted search in e-commerce, doesn't work well for text document retrieval, due to the incompleteness (low recall) of metadata assignment in semi-structured text documents. Instead, a soft model performs more effectively. The faceted feedback mechanism can also be combined with document-based relevance feedback and pseudo relevance feedback to further improve the retrieval performance.

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    cover image ACM Conferences
    SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
    July 2010
    944 pages
    ISBN:9781450301534
    DOI:10.1145/1835449
    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: 19 July 2010

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    Author Tags

    1. faceted feedback
    2. interactive retrieval
    3. metadata-based retrieval
    4. relevance feedback

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    • (2024)Cross-Modal Retrieval: A Systematic Review of Methods and Future DirectionsProceedings of the IEEE10.1109/JPROC.2024.3525147112:11(1716-1754)Online publication date: Nov-2024
    • (2022)Guided Text-based Item ExplorationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557141(3410-3420)Online publication date: 17-Oct-2022
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