• DocumentCode
    2968897
  • Title

    Achieving Classification and Clustering in One Shot Lesson Learned from Labeling Anonymous Datasets

  • Author

    Ahmed, Emdad

  • Author_Institution
    Dept. of Comput. Sci., Integration Inf. Lab., Wayne State Univ., Detroit, MI, USA
  • fYear
    2010
  • fDate
    22-24 Sept. 2010
  • Firstpage
    228
  • Lastpage
    231
  • Abstract
    This paper presents an algorithm LadsComplete which is able to automatically assign label for HTML tabular web data, depending on syntactical similarities between elements of the table. We categorize columns into three types: Disjoint Set Column (DSC), Repeated Prefix / Suffix Column (RPS) and Numeric Column (NUM). For labeling DSC column, our method rely on hits count from web search engine. Experimental results from large number of sites in different domains and subjective evaluation show that the proposed algorithm works fairly well. We hypothesize that our algorithm LadsComplete will do a good job for autonomous label assignment. We are NOT aware of any such prior work that address to connect two orthogonal research viz. wrapper generation and label extraction for value added services such as online comparison shopping.
  • Keywords
    Internet; pattern classification; pattern clustering; search engines; LadsComplete algorithm; Web search engine; anonymous dataset labeling; disjoint set column type; numeric column type; pattern classification; pattern clustering; repeated prefix-suffix column type; Books; Data mining; Engines; HTML; Labeling; Motion pictures; Web search; HTML Table; Hidden Web; Web Form; Wrapper;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2010 IEEE Fourth International Conference on
  • Conference_Location
    Pittsburgh, PA
  • Print_ISBN
    978-1-4244-7912-2
  • Electronic_ISBN
    978-0-7695-4154-9
  • Type

    conf

  • DOI
    10.1109/ICSC.2010.81
  • Filename
    5629134