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"Is Sven Seven?": A Search Intent Module for Children

Published:07 July 2016Publication History

ABSTRACT

The Internet is the biggest data-sharing platform, comprised of an immeasurable quantity of resources covering diverse topics appealing to users of all ages. Children shape tomorrow's society, so it is essential that this audience becomes agile with searching information. Although young users prefer well-known search engines, their lack of skill in formulating adequate queries and the fact that search tools were not designed explicitly with children in mind, can result in poor outcomes. The reasons for this include children's limited vocabulary, which makes it challenging to articulate information needs using short queries, or their tendency to create queries that are too long, which translates to few or irrelevant retrieved results. To enhance web search environments in response to children's behaviors and expectations, in this paper we discuss an initial effort to verify well-known issues, and identify yet to be explored ones, that affect children in formulating (natural language or keyword) queries. We also present a novel search intent module developed in response to these issues, which can seamlessly be integrated with existing search engines favored by children. The proposed module interprets a child's query and creates a shorter and more concise query to submit to a search engine, which can lead to a more successful search session. Initial experiments conducted using a sample of children queries validate the correctness of the proposed search intent module.

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          cover image ACM Conferences
          SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
          July 2016
          1296 pages
          ISBN:9781450340694
          DOI:10.1145/2911451

          Copyright © 2016 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 7 July 2016

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          SIGIR '16 Paper Acceptance Rate62of341submissions,18%Overall Acceptance Rate792of3,983submissions,20%

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