• DocumentCode
    244700
  • Title

    Title named entity recognition using wikipedia and abbreviation generation

  • Author

    Youngmin Park ; Sangwoo Kang ; Jungyun Seo

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Sogang Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    15-17 Jan. 2014
  • Firstpage
    169
  • Lastpage
    172
  • Abstract
    In this paper, we propose a title named entity recognition model using Wikipedia and abbreviation generation. The proposed title named entity recognition model automatically extracts title named entities from Wikipedia so constant renewal is possible without additional costs. Also, in order to establish a dictionary of title named entity abbreviations, generation rules are used to generate abbreviation candidates and abbreviations are selected through web search methods. In this paper, we propose a statistical model that recognizes title named entities using CRFs (Conditional Random Fields). The proposed model uses lexical information, a named entity dictionary, and an abbreviation dictionary, and provides title named entity recognition performance of 82.1% according to experimental results.
  • Keywords
    Web sites; information retrieval; random processes; statistical analysis; text analysis; CRF; Web search methods; Wikipedia; abbreviation generation; automatic title named entity extraction; conditional random fields; generation rules; lexical information; statistical model; title named entity abbreviation dictionary; title named entity recognition; title named entity recognition model; Dictionaries; Educational institutions; Electronic publishing; Encyclopedias; Internet; Syntactics; Abbreviation generation; Conditional random field; Title named entity; Wikipedia;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Smart Computing (BIGCOMP), 2014 International Conference on
  • Conference_Location
    Bangkok
  • Type

    conf

  • DOI
    10.1109/BIGCOMP.2014.6741430
  • Filename
    6741430