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Interactive Topic Search System Based on Topic Cluster Technology

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  • Lin-Chih Chen

    (National Dong Hwa University)

Abstract

In this paper, we develop an interactive hierarchical topic search system. In our system, the generation of topic names is mainly based on the N-gram statistical language model. The construction of hierarchical tree relationships between topics is mainly based on the concept of mathematical sets. In this study, the concept of mathematical sets not only helps the system to construct a topic hierarchy tree quickly, but also allows different users to use different binary operations to generate different interactive search results. In general, this study has the following three advantages. First, the generated topic names are presented in a hierarchical form rather than a flat form. Secondly, the interactive search for this study was achieved by non-stored user search and click history. Therefore, our approach can avoid personal privacy and large storage space issues. Finally, the concept of mathematical sets not only allows us to generate topic trees in linear time, but also allows users to run all possible binary operations to meet various interactive search needs.

Suggested Citation

  • Lin-Chih Chen, 0. "Interactive Topic Search System Based on Topic Cluster Technology," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
  • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-020-10021-8
    DOI: 10.1007/s10796-020-10021-8
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    References listed on IDEAS

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    1. Min Song & Il-Yeol Song & Peter P. Chen, 2004. "Design and Development of a Cross Search Engine for Multiple Heterogeneous Databases Using UML and Design Patterns," Information Systems Frontiers, Springer, vol. 6(1), pages 77-90, March.
    2. Mehmet N. Aydin & N. Ziya Perdahci, 2019. "Dynamic network analysis of online interactive platform," Information Systems Frontiers, Springer, vol. 21(2), pages 229-240, April.
    3. Mehmet N. Aydin & N. Ziya Perdahci, 0. "Dynamic network analysis of online interactive platform," Information Systems Frontiers, Springer, vol. 0, pages 1-12.
    4. Disha Verma & Kanika Minocha & Barjesh Kochar, 2014. "A Multi-Agent Based Personalized Search Engine with Topical Crawling Capabilities," The IUP Journal of Computer Sciences, IUP Publications, vol. 0(3), pages 20-33, July.
    5. David Laniado & Yana Volkovich & Salvatore Scellato & Cecilia Mascolo & Andreas Kaltenbrunner, 2018. "The Impact of Geographic Distance on Online Social Interactions," Information Systems Frontiers, Springer, vol. 20(6), pages 1203-1218, December.
    6. Ozgur Turetken & Ramesh Sharda, 2005. "Clustering-Based Visual Interfaces for Presentation of Web Search Results: An Empirical Investigation," Information Systems Frontiers, Springer, vol. 7(3), pages 273-297, July.
    7. Girish Keshav Palshikar & Manoj Apte & Deepak Pandita, 2018. "Weakly Supervised and Online Learning of Word Models for Classification to Detect Disaster Reporting Tweets," Information Systems Frontiers, Springer, vol. 20(5), pages 949-959, October.
    8. Jorge Martinez-Gil & José F. Aldana-Montes, 2013. "Semantic similarity measurement using historical google search patterns," Information Systems Frontiers, Springer, vol. 15(3), pages 399-410, July.
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