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Volumn 4683 LNCS, Issue , 2007, Pages 435-443

Instant message clustering based on extended vector space model

Author keywords

Instant messages clustering; k means; Vector space model

Indexed keywords

COMPUTATIONAL EFFICIENCY; DATABASE SYSTEMS; MESSAGE PASSING; VECTOR QUANTIZATION;

EID: 38049011433     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74581-5_48     Document Type: Conference Paper
Times cited : (24)

References (13)
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  • 2
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  • 3
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    • Quantifying Semantic Similarity of Chinese Words from Hownet
    • Beijing, IEEE Computer Society Press, Los Alamitos
    • Guan, Y., et al.: Quantifying Semantic Similarity of Chinese Words from Hownet. In: IEEE Proceedings of ICMLC02, Beijing, vol. 1, pp. 234-239. IEEE Computer Society Press, Los Alamitos (2002)
    • (2002) IEEE Proceedings of ICMLC02 , vol.1 , pp. 234-239
    • Guan, Y.1
  • 6
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    • Hearst, M.A.: TextTiling: A Quantitative Approach to Discourse Segmentation, Technical Report UCB: S2K-93-24 (1993)
    • Hearst, M.A.: TextTiling: A Quantitative Approach to Discourse Segmentation, Technical Report UCB: S2K-93-24 (1993)
  • 8
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    • A probabilistic model for dimensionality reduction in information retrieval and filtering
    • Raleigh, NC
    • Ding, C.H.Q.: A probabilistic model for dimensionality reduction in information retrieval and filtering. In: Proc. of the 1st SIAM, Raleigh, NC (2000)
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    • Ding, C.H.Q.1
  • 11
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    • Hotho, A., et al.: Ontology-based Text Document Clustering. KI 16(4), 48-54 (2002)
    • Hotho, A., et al.: Ontology-based Text Document Clustering. KI 16(4), 48-54 (2002)
  • 12
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    • Cluster ensembles - a knowledge reuse framework for combining partitions
    • Strehl, A., Ghosh, J.: Cluster ensembles - a knowledge reuse framework for combining partitions. Journal of Machine Learning Research 3, 583-617 (2002)
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    • Strehl, A.1    Ghosh, J.2
  • 13
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    • An algorithm for suffix stripping
    • Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130-137 (1980)
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.