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Heading-Aware Snippet Generation for Web Search

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Information Retrieval Technology (AIRS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9460))

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Abstract

We propose heading-aware methods of generating search result snippets of web pages. A heading is a brief description of the topic of its associated sentences. Some existing methods give priority to sentences containing many words that also appear in headings when selecting sentences to be included in snippets with limited length. However, according to our observation, words in heading are very often omitted from their associated sentences because readers can understand the topic of the sentences by reading their heading. To score sentences considering such omission, our methods count keyword occurrences in their headings as well as in the sentences themselves. Our evaluation result indicated that our methods were effective only for queries with clear intents or containing four or more keywords. To discuss the statistical significance of the result, another evaluation with more queries is needed.

T. Manabe—Research Fellow of Japan Society for the Promotion of Science.

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Acknowledgment

This work was supported by JSPS KAKENHI Grant Number 13J06384, 26540163.

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Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Sakyo, Kyoto, 606-8501, Japan

    Tomohiro Manabe & Keishi Tajima

Authors
  1. Tomohiro Manabe
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  2. Keishi Tajima
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Corresponding author

Correspondence to Tomohiro Manabe .

Editor information

Editors and Affiliations

  1. Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia

    Guido Zuccon

  2. Brisbane, Queensland, Australia

    Shlomo Geva

  3. University of Tsukuba, Ibaraki, Japan

    Hideo Joho

  4. RMIT University, Melbourne, Australia

    Falk Scholer

  5. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Aixin Sun

  6. Tianjin University, China

    Peng Zhang

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Manabe, T., Tajima, K. (2015). Heading-Aware Snippet Generation for Web Search. In: Zuccon, G., Geva, S., Joho, H., Scholer, F., Sun, A., Zhang, P. (eds) Information Retrieval Technology. AIRS 2015. Lecture Notes in Computer Science(), vol 9460. Springer, Cham. https://doi.org/10.1007/978-3-319-28940-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-28940-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28939-7

  • Online ISBN: 978-3-319-28940-3

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