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Aggregating Web Search Results

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Intelligent Information and Database Systems (ACIIDS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11431))

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Abstract

In this paper a method for aggregating Web search results is proposed. The aggregator results are compared with the results of most popular search engines: Google, Bing and Yandex. There are 3 stages of the comparison, one for each of the languages: English, Polish and Russian. The quality of the aggregator search results is tested based on user preferences and measured with normalized discounted cumulative gain (nDCG).

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, wybrzeze Wyspiańskiego 27, 50-370, Wroclaw, Poland

    Marek Kopel & Maksim Buben

Authors
  1. Marek Kopel
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  2. Maksim Buben
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Corresponding author

Correspondence to Marek Kopel .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Bina Nusantara University, Jakarta, Indonesia

    Ford Lumban Gaol

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Kopel, M., Buben, M. (2019). Aggregating Web Search Results. In: Nguyen, N., Gaol, F., Hong, TP., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science(), vol 11431. Springer, Cham. https://doi.org/10.1007/978-3-030-14799-0_16

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  • DOI: https://doi.org/10.1007/978-3-030-14799-0_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14798-3

  • Online ISBN: 978-3-030-14799-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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