earticle

논문검색

The Topic Detection and Tracking with Topic Sensitive Language Model

원문정보

Ruifang He, Bing Qin, Ting Liu, Sheng Li

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

In this paper, we explore the language model with topic sensitive features for the topic
detection and tracking, formulate the relationship among the Chinese internet new words, language model with topic sensitive feature and the scheduling logic and the interval temporal
reasoning and the key techniques. we use the Chinese internet new words to strengthen the
detection and tracking of the topic and try to employ the scheduling logic and interval temporal
reasoning to educe the reciprocal influences of events. At last we summarize the potential issues
and the future work.

목차

Abstract
 1. Motivation
 2. Related research of the TDT(Allan 1998,Wayne 2005, Fiscus 2004)
  2.1 Concise History
  2.2 Goal and Value
  2.3 Main Task of TDT and Our Work
 3. The Primary Ideas and the Plan Graph of theTask
 4. The Key Techniques
  4.1 Internet New Methods Recognition (Zou 2004)
  4.2 The Language Model With Topic SensitiveFeatures
  4.3 Scheduling Logic And The Interval TemporalLogic Reasoning
 5. The Conclusion and the Future Work
 References

저자정보

  • Ruifang He Information Retrieval Laboratory, School of Computer Science & Technology, Harbin Institute of Technology
  • Bing Qin Information Retrieval Laboratory, School of Computer Science & Technology, Harbin Institute of Technology
  • Ting Liu Information Retrieval Laboratory, School of Computer Science & Technology, Harbin Institute of Technology
  • Sheng Li Information Retrieval Laboratory, School of Computer Science & Technology, Harbin Institute of Technology

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 기관로그인 시 무료 이용이 가능합니다.
      ※ 학술발표대회집, 워크숍 자료집 중 4페이지 이내 논문은 '요약'만 제공되는 경우가 있으니, 구매 전에 간행물명, 페이지 수 확인 부탁 드립니다.

      • 4,000원

      0개의 논문이 장바구니에 담겼습니다.