• DocumentCode
    2198668
  • Title

    Greedy-Algorithm of KSORD Supporting Multi-language Phrase Recognition

  • Author

    Li, Peng ; Zhu, Qing ; Tian, Chao ; Wang, Shan

  • Author_Institution
    Key Lab. of Data Eng. & Knowledge Eng. Sch. of Inf., Renmin Univ. of China, Beijing
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    205
  • Lastpage
    209
  • Abstract
    With the rapid development of information retrieval technology and daily increasing information in the Internet, common users can retrieve many text-based database and get part of the information through the search engines such as Google, and Baidu. However, there is a great amount of data contained in the background relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison between our algorithm and the existing ones. The experiment results shows that our algorithm owns not only the feature of effectiveness but also the feature of efficiency.
  • Keywords
    Internet; computational linguistics; data structures; dictionaries; greedy algorithms; information retrieval; natural language processing; relational databases; search engines; text analysis; Internet; Web page; data structure; greedy algorithm; information retrieval technology; multilanguage phrase recognition; multiple dictionary; relational database; search engine; text-based database; Chaos; Data engineering; Data structures; Dictionaries; Information retrieval; Internet; Knowledge engineering; Laboratories; Relational databases; Search engines; greedy algorithm; keyword search; relational database;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering, 2008. ICACTE '08. International Conference on
  • Conference_Location
    Phuket
  • Print_ISBN
    978-0-7695-3489-3
  • Type

    conf

  • DOI
    10.1109/ICACTE.2008.38
  • Filename
    4736951