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Volumn , Issue , 2007, Pages 207-214

Analyzing feature trajectories for event detection

Author keywords

DFT; Event detection; Feature categorization; Gaussian

Indexed keywords

ALGORITHMS; DATA ACQUISITION; INFORMATION RETRIEVAL SYSTEMS; PROBLEM SOLVING; SPECTRUM ANALYSIS;

EID: 36448936021     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1277741.1277779     Document Type: Article
Times cited : (195)

References (21)
  • 3
    • 84878945448 scopus 로고    scopus 로고
    • Reuters corpus, http://www.reuters.com/researchandstandards/corpus/.
    • Reuters corpus
  • 5
    • 85109214302 scopus 로고    scopus 로고
    • First story detection in tdt is hard
    • J. Allan, V. Lavrenko, and H. Jin. First story detection in tdt is hard. In CIKM, pages 374-381, 2000.
    • (2000) CIKM , pp. 374-381
    • Allan, J.1    Lavrenko, V.2    Jin, H.3
  • 6
    • 1542317680 scopus 로고    scopus 로고
    • Retrieval and novelty detection at the sentence level
    • J. Allan, C. Wade, and A. Bolivar. Retrieval and novelty detection at the sentence level. In SIGIR, pages 314-321, 2003.
    • (2003) SIGIR , pp. 314-321
    • Allan, J.1    Wade, C.2    Bolivar, A.3
  • 7
    • 1542377531 scopus 로고    scopus 로고
    • A system for new event detection
    • T. Brants, F. Chen, and A. Farahat. A system for new event detection. In SIGIR, pages 330-337, 2003.
    • (2003) SIGIR , pp. 330-337
    • Brants, T.1    Chen, F.2    Farahat, A.3
  • 9
    • 33745624002 scopus 로고    scopus 로고
    • Parameter free bursty events detection in text streams
    • G. P. C. Fung, J. X. Yu, P. S. Yu, and H. Lu. Parameter free bursty events detection in text streams. In VLDB, pages 181-192, 2005.
    • (2005) VLDB , pp. 181-192
    • Fung, G.P.C.1    Yu, J.X.2    Yu, P.S.3    Lu, H.4
  • 10
    • 33845208661 scopus 로고    scopus 로고
    • A model for anticipatory event detection
    • Q. He, K. Chang, and E.-P. Lim. A model for anticipatory event detection. In ER, pages 168-181, 2006.
    • (2006) ER , pp. 168-181
    • He, Q.1    Chang, K.2    Lim, E.-P.3
  • 11
    • 70350718061 scopus 로고    scopus 로고
    • Q. He, K. Chang, E.-P. Lim, and J. Zhang. Bursty feature reprensentation for clustering text streams. In SDM, accepted, 2007.
    • Q. He, K. Chang, E.-P. Lim, and J. Zhang. Bursty feature reprensentation for clustering text streams. In SDM, accepted, 2007.
  • 12
    • 0242540464 scopus 로고    scopus 로고
    • Bursty and hierarchical structure in streams
    • J. Kleinberg. Bursty and hierarchical structure in streams. In SIGKDD, pages 91-101, 2002.
    • (2002) SIGKDD , pp. 91-101
    • Kleinberg, J.1
  • 13
    • 14844347603 scopus 로고    scopus 로고
    • On the bursty evolution of blogspace
    • R. Kumar, J. Novak, P. Raghavan, and A. Tomkins. On the bursty evolution of blogspace. In WWW, pages 159-178, 2005.
    • (2005) , pp. 159-178
    • Kumar, R.1    Novak, J.2    Raghavan, P.3    Tomkins, A.4
  • 14
    • 8644246887 scopus 로고    scopus 로고
    • Text classification and named entities for new event detection
    • G. Kumaran and J. Allan. Text classification and named entities for new event detection. In SIGIR, pages 297-304, 2004.
    • (2004) SIGIR , pp. 297-304
    • Kumaran, G.1    Allan, J.2
  • 15
    • 29244457315 scopus 로고    scopus 로고
    • Discovering evolutionary theme patterns from text: An exploration of temporal text mining
    • Q. Mei and C. Zhai. Discovering evolutionary theme patterns from text: an exploration of temporal text mining. In SIGKDD, pages 198-207, 2005.
    • (2005) SIGKDD , pp. 198-207
    • Mei, Q.1    Zhai, C.2
  • 16
    • 33746903236 scopus 로고    scopus 로고
    • Kullback-liebler divergences of normal, gamma, dirichlet and wishart densities
    • Technical report
    • W. D. Penny. Kullback-liebler divergences of normal, gamma, dirichlet and wishart densities. Technical report, 2001.
    • (2001)
    • Penny, W.D.1
  • 17
    • 0034795524 scopus 로고    scopus 로고
    • Combining semantic and syntactic document classifiers to improve first story detection
    • N. Stokes and J. Carthy. Combining semantic and syntactic document classifiers to improve first story detection. In SIGIR, pages 424-425, 2001.
    • (2001) SIGIR , pp. 424-425
    • Stokes, N.1    Carthy, J.2
  • 18
    • 0033645893 scopus 로고    scopus 로고
    • Automatic generation of overview timelines
    • R. Swan and J. Allan. Automatic generation of overview timelines. In SIGIR, pages 49-56, 2000.
    • (2000) SIGIR , pp. 49-56
    • Swan, R.1    Allan, J.2
  • 19
    • 3142717571 scopus 로고    scopus 로고
    • Identifying similarities, periodicities and bursts for online search queries
    • M. Vlachos, C. Meek, Z. Vagena, and D. Gunopulos. Identifying similarities, periodicities and bursts for online search queries. In SIGMOD, pages 131-142, 2004.
    • (2004) SIGMOD , pp. 131-142
    • Vlachos, M.1    Meek, C.2    Vagena, Z.3    Gunopulos, D.4
  • 20
    • 0032264627 scopus 로고    scopus 로고
    • A study of retrospective and on-line event detection
    • Y. Yang, T. Pierce, and J. Carbonell. A study of retrospective and on-line event detection. In SIGIR, pages 28-36, 1998.
    • (1998) SIGIR , pp. 28-36
    • Yang, Y.1    Pierce, T.2    Carbonell, J.3
  • 21
    • 0242456762 scopus 로고    scopus 로고
    • Topic-conditioned novelty detection
    • Y. Yang, J. Zhang, J. Carbonell, and C. Jin. Topic-conditioned novelty detection. In SIGKDD, pages 688-693, 2002.
    • (2002) SIGKDD , pp. 688-693
    • Yang, Y.1    Zhang, J.2    Carbonell, J.3    Jin, C.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.