ESpotter: Adaptive Named Entity Recognition for Web Browsing

نویسندگان

  • Jianhan Zhu
  • Victoria S. Uren
  • Enrico Motta
چکیده

Web users are facing information overload problems, i.e., it is hard for them to find desired information on the web. Hence the growing interest in named entity recognition (NER) for discovering relevant information on users’ behalf. We present a browser plug-in called ESpotter which adapts lexicons and patterns to a domain hierarchy consisting of domains on the web and user preferences for accurate and efficient NER. Mappings are created from domain independent types to domain specific types. Entities are highlighted according to their types, and users are assisted by navigational functionalities between these highlighted entities.

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تاریخ انتشار 2005