Instance based clustering of semantic web resources

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5021 LNCS, Issue , 2008, Pages 303-317

  Grimnes, Gunnar Aastrand ^a   Edwards, Peter ^b   Preece, Alun ^c  

^a GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

^b UNIVERSITY OF ABERDEEN   (United Kingdom)

^c CARDIFF UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMOUS AGENTS; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; COMPUTATIONAL GEOMETRY; EXTRACTION; FLOW OF SOLIDS; INFORMATION THEORY; INTELLIGENT AGENTS; SEMANTIC WEB; SEMANTICS; SET THEORY; SOLVENT EXTRACTION; STABILIZERS (AGENTS); WORLD WIDE WEB;

DATA-SETS; ESSENTIAL FEATURE; EUROPEAN; EVALUATION METRICS; EXTRACTION METHODS; HEIDELBERG (CO); INTELLIGENT AUTONOMOUS AGENTS; RELATIONAL DATABASES; SEMANTIC WEB DATA; SEMANTIC WEB VISION; SIMILARITY METRIC; SPRINGER (CO); WEB RESOURCES;

MULTI AGENT SYSTEMS;

EID: 45449098678     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68234-9_24     Document Type: Conference Paper

References (14)

1. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284, 28-37 (2001)
2. Grimnes, G.A., Edwards, P., Preece, A.: Learning Meta-Descriptions of the FOAF Network. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 152-165. Springer, Heidelberg (2004)
3. Edwards, P., Grimnes, G.A., Preece, A.: An Empirical Investigation of Learning from the Semantic Web. In: ECML/PKDD, Semantic Web Mining Workshop, pp. 71-89 (2002)
4. Johnson, S.C.: Hierarchical clustering schemes. Psychometrika 2, 241-254 (1967)
5. Sauermann, L., Grimnes, G.A., Kiesel, M., Fluit, C., Maus, H., Heim, D., Nadeem, D., Ho-rak, B., Dengel, A.: Semantic desktop 2.0: The gnowsis experience. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, Springer, Heidelberg (2006)
6. Montes-y-Gómez, M., Gelbukh, A., López-López, A.: Comparison of Conceptual Graphs. In: Cairó, O., Cantú, F.J. (eds.) MICAI 2000. LNCS, vol. 1793, pp. 548-556. Springer, Heidelberg (2000)
7. Dieng, R., Hug, S.: Comparison of personal ontologies represented through conceptual graphs. In: Proceedings of ECAI 1998, pp. 341-345 (1998)
8. Euzenat, J., Valtchev, P.: An integrative proximity measure for ontology alignment. In: Proceedings of the 1st Intl. Workshop on Semantic Integration. CEUR, vol. 82 (2003)
9. Maedche, A., Zacharias, V.: Clustering ontology-based metadata in the semantic web. In: Elomaa, T., Mannila, H., Toivonen, H. (eds.) PKDD 2002. LNCS (LNAI), vol. 2431, pp. 348-360. Springer, Heidelberg (2002)
10. Strehl, A.: Relationship-based Clustering and Cluster Ensembles for High-dimensional Data Mining. PhD thesis, The University of Texas at Austin (2002)
11. Larsen, B., Aone, C.: Fast and effective text mining using linear-time document clustering. In: KDD 1999: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 16-22. ACM Press, New York (1999)
12. Heß, A.: Supervised and Unsupervised Ensemble Learning for the Semantic Web. PhD thesis, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland (2006)
13. Zamir, O., Etzioni, O., Madani, O., Karp, R.M.: Fast and intuitive clustering of web documents. In: KDD, pp. 287-290 (1997)
14. Sugar, C.A., James, G.M.: Finding the Number of Clusters in a Data Set - An Information Theoretic Approach. Journal of the American Statistical Association 98, 750-763 (2003)