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Volumn 4426 LNAI, Issue , 2007, Pages 1072-1079

Geo-spatial clustering with non-spatial attributes and geographic non-overlapping constraint: A penalized spatial distance measure

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; KNOWLEDGE ENGINEERING; PROBLEM SOLVING;

EID: 38049127392     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71701-0_121     Document Type: Conference Paper
Times cited : (12)

References (10)
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    • 0036709106 scopus 로고    scopus 로고
    • CLARANS: A method for clustering objects for spatial data mining
    • Pages
    • R. Ng, J. Han: CLARANS: A method for clustering objects for spatial data mining. IEEE Trans. on Knowledge and Data Engineering. 14 (2002). Pages: 1003-1016.
    • (2002) IEEE Trans. on Knowledge and Data Engineering , vol.14 , pp. 1003-1016
    • Ng, R.1    Han, J.2
  • 3
    • 0035013804 scopus 로고    scopus 로고
    • Spatial clustering in the presence of obstacles
    • Pages
    • Tung A. K. H., Hou J. and Han J.: Spatial clustering in the presence of obstacles. In Proc. of ICDE'01. Pages: 359-367.
    • Proc. of ICDE'01 , pp. 359-367
    • Tung, A.K.H.1    Hou, J.2    Han, J.3
  • 4
    • 0003136237 scopus 로고    scopus 로고
    • Efficient and Effective Clustering Methods for Spatial Data Mining
    • Pages
    • R. Ng, J. Han: Efficient and Effective Clustering Methods for Spatial Data Mining. In Proc. of VLDB'94. Pages: 144-155.
    • Proc. of VLDB'94 , pp. 144-155
    • Ng, R.1    Han, J.2
  • 7
    • 85170282443 scopus 로고    scopus 로고
    • A density-based algorithm for discovering clusters in large spatial databases with noise
    • Pages
    • M. Ester, H.-P. Kriegel, J. Sander and X. Xu: A density-based algorithm for discovering clusters in large spatial databases with noise. In Proc. of SIGKDD'96 Pages: 226-231
    • Proc. of SIGKDD'96 , pp. 226-231
    • Ester, M.1    Kriegel, H.-P.2    Sander, J.3    Xu, X.4
  • 9
    • 7444269028 scopus 로고    scopus 로고
    • DBRS: A Density-Based Spatial Clustering Method with Random Sampling
    • Pages
    • Xin Wang and H. J. Hamilton: DBRS: A Density-Based Spatial Clustering Method with Random Sampling. In Proc. of PAKDD'03. Pages: 563-575
    • Proc. of PAKDD'03 , pp. 563-575
    • Wang, X.1    Hamilton, H.J.2
  • 10
    • 35048839919 scopus 로고    scopus 로고
    • Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators
    • Pages
    • Xin Wang, C. Rostoker, H. J. Hamilton: Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators. In Proc. of PKDD'04. Pages: 446-458.
    • Proc. of PKDD'04 , pp. 446-458
    • Xin Wang, C.1    Rostoker, H.2    Hamilton, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.