• DocumentCode
    243604
  • Title

    Introduction of Search Engine Focusing on Trend-Related Queries to Market of Data

  • Author

    Yanjun Zhu ; Takama, Yasufumi ; Kato, Yu ; Kori, Shogo ; Ishikawa, Hiroshi

  • Author_Institution
    Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Tokyo, Japan
  • fYear
    2014
  • fDate
    14-14 Dec. 2014
  • Firstpage
    511
  • Lastpage
    516
  • Abstract
    This paper introduces a search engine that is designed for answering trend-related queries, and discuss its applicability to market of data. Huge amount of information provided by various data resources is available on the Web, which are usually accessed with Web search engines. Although a Web search engine is a necessary tool for us, we think that there is a significant difference between function provided by existing search engines and users´ information needs. Aiming at narrowing the gap, we are developing advanced search engine that focuses on the task of answering trend-related queries. By focusing on the specific task, more advanced search functions can be provided compared with existing Web search engines. As the task of answering trend-related queries is supposed to be common in various domains, we expect it could be used for various purposes. We think the market of data is one of promising target domain for the proposed search engine, because it can be used for finding connection between different data resources in terms of temporal trend. This paper describes the proposed search engine, and shows an experimental result with test participants and some examples of finding relationship among different data resources.
  • Keywords
    Internet; information needs; query processing; search engines; Web search engine; Worl Wide Web; data resource; search function; trend-related query; user information need; Bicycles; Engines; Google; Market research; Search engines; Silicon; Web search; market of data; search engine; trend information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4799-4275-6
  • Type

    conf

  • DOI
    10.1109/ICDMW.2014.67
  • Filename
    7022639