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Semantic search via XML fragments: a high-precision approach to IR

Published: 06 August 2006 Publication History

Abstract

In some IR applications, it is desirable to adopt a high precision search strategy to return a small set of documents that are highly focused and relevant to the user's information need. With these applications in mind, we investigate semantic search using the XML Fragments query language on text corpora automatically pre-processed to encode semantic information useful for retrieval. We identify three XML Fragment operations that can be applied to a query to conceptualize, restrict, or relate terms in the query. We demonstrate how these operations can be used to address four different query-time semantic needs: to specify target information type, to disambiguate keywords, to specify search term context, or to relate select terms in the query. We demonstrate the effectiveness of our semantic search technology through a series of experiments using the two applications in which we embed this technology and show that it yields significant improvement in precision in the search results.

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    cover image ACM Conferences
    SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
    August 2006
    768 pages
    ISBN:1595933697
    DOI:10.1145/1148170
    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: 06 August 2006

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    Author Tags

    1. XML retrieval
    2. question answering
    3. semantic search

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    SIGIR06: The 29th Annual International SIGIR Conference
    August 6 - 11, 2006
    Washington, Seattle, USA

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

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    Cited By

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    • (2023)Olio: A Semantic Search Interface for Data RepositoriesProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606806(1-16)Online publication date: 29-Oct-2023
    • (2019)Bridging Text Visualization and Mining: A Task-Driven SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.283434125:7(2482-2504)Online publication date: 1-Jul-2019
    • (2018)Cost-effective conceptual design using taxonomiesThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0501-127:3(369-394)Online publication date: 1-Jun-2018
    • (2017)A Review of the State of the Art in Hindi Question Answering SystemsIntelligent Natural Language Processing: Trends and Applications10.1007/978-3-319-67056-0_14(265-292)Online publication date: 18-Nov-2017
    • (2015)Cost-Effective Conceptual Design for Information ExtractionACM Transactions on Database Systems10.1145/271632140:2(1-39)Online publication date: 30-Jun-2015
    • (2014)Which concepts are worth extracting?Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data10.1145/2588555.2610496(779-790)Online publication date: 18-Jun-2014
    • (2014)New Dimensions in Semantic Knowledge ManagementTowards the Internet of Services: The THESEUS Research Program10.1007/978-3-319-06755-1_4(37-50)Online publication date: 2-Jul-2014
    • (2013)Semantic Search Engine and Object Database Guidelines for Service Oriented Architecture ModelsTechnology Diffusion and Adoption10.4018/978-1-4666-2791-8.ch015(225-250)Online publication date: 2013
    • (2013)Repeatable and reliable semantic search evaluationWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2013.05.00521(14-29)Online publication date: 1-Aug-2013
    • (2013)A Linked Science investigation: enhancing climate change data discovery with semantic technologiesEarth Science Informatics10.1007/s12145-013-0118-26:3(175-185)Online publication date: 21-Jun-2013
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