Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration

Shoichi Nakamura, Takuya Matsumoto, Hiroki Nakayama, Ryo Onuma, Hiroaki Kaminaga, Youzou Miyadera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Complicated Web exploration involving trial and error is quite important in intellectual creative activities. To successfully conduct such exploration, each user needs to satisfactorily understand the results and circumstances (i.e., contexts) of his/her own exploration. However, the contexts are difficult for a user to understand since queries and the pages obtained with them increase rapidly as exploration progresses. In this research, we were aiming at developing methods for visualizing the contexts so that a user can easily understand them. This paper mainly describes methods for clustering queries and extracting the transitions of search queries by analyzing the relationships between the clusters of queries. Moreover, this paper also describes a prototype of context map with some screenshots.

Original languageEnglish
Title of host publicationProceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017
PublisherAssociation for Computing Machinery
Pages227-231
Number of pages5
ISBN (Electronic)9781450353922
DOIs
Publication statusPublished - 2017 Dec 5
Event2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017 - Jakarta, Indonesia
Duration: 2017 Dec 52017 Dec 7

Other

Other2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017
CountryIndonesia
CityJakarta
Period17/12/517/12/7

Keywords

  • Complicated Web exploration
  • Context map
  • Exploration contexts
  • Transitions of search queries
  • Visualization of contexts

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Nakamura, S., Matsumoto, T., Nakayama, H., Onuma, R., Kaminaga, H., & Miyadera, Y. (2017). Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration. In Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017 (pp. 227-231). Association for Computing Machinery. https://doi.org/10.1145/3168390.3168419

Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration. / Nakamura, Shoichi; Matsumoto, Takuya; Nakayama, Hiroki; Onuma, Ryo; Kaminaga, Hiroaki; Miyadera, Youzou.

Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017. Association for Computing Machinery, 2017. p. 227-231.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nakamura, S, Matsumoto, T, Nakayama, H, Onuma, R, Kaminaga, H & Miyadera, Y 2017, Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration. in Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017. Association for Computing Machinery, pp. 227-231, 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017, Jakarta, Indonesia, 17/12/5. https://doi.org/10.1145/3168390.3168419
Nakamura S, Matsumoto T, Nakayama H, Onuma R, Kaminaga H, Miyadera Y. Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration. In Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017. Association for Computing Machinery. 2017. p. 227-231 https://doi.org/10.1145/3168390.3168419
Nakamura, Shoichi ; Matsumoto, Takuya ; Nakayama, Hiroki ; Onuma, Ryo ; Kaminaga, Hiroaki ; Miyadera, Youzou. / Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration. Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017. Association for Computing Machinery, 2017. pp. 227-231
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