A clustering technique for news articles using WordNet

Knowledge-Based Systems

Volumn 36, Issue , 2012, Pages 115-128

  Bouras, Christos ^a,b   Tsogkas, Vassilis ^a,b  

^a University of Patras and Computer Technology Institute   (Greece)

^b UNIVERSITY OF PATRAS   (Greece)

Author keywords

Cluster labeling; k Means; News clustering; Partitional clustering; W k means

Indexed keywords

CLUSTER LABELING; K-MEANS; NEWS CLUSTERING; PARTITIONAL CLUSTERING; W-K MEANS;

CLUSTER ANALYSIS; ONTOLOGY;

CLUSTERING ALGORITHMS;

EID: 84867881965     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.06.015     Document Type: Article

References (26)

1. A.A. Abdelmalek, E. Zakaria, and S. Michel Evaluation of text clustering methods using WordNet The International Arab Journal of Information Technology 7 4 2010
2. A.Y. Al-Omary, and M.S. Jamil A new approach of clustering based machine-learning algorithm Knowledge-Based Systems 19 4 2006 248 258
3. D. Arthur, S. Vassilvitskii, On the Worst Case Complexity of the k-means Method, Technical Report, Stanford, 2005.
4. D. Arthur, S. Vassilvitskii, k-Means++: the advantages of careful seeding, in: Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007, pp. 1027-1035.
5. C. Bouras, V. Poulopoulos, and V. Tsogkas PeRSSonal's core functionality evaluation: enhancing text labeling through personalized summaries Data and Knowledge Engineering Journal 64 1 2008 330 345 (Elsevier Science)
6. C. Bouras, and V. Tsogkas Improving text summarization using noun retrieval techniques, Lecture Notes in Computer Science Knowledge-Based Intelligent Information and Engineering Systems 5178 2008 593 600
7. P.S. Bradley, U. Fayyad, Refining initial points for k-means clustering, in: Proceedings of the 15th International Conference on Machine Learning, 1998, pp. 91-99.
8. D. Carmel, H. Roitman, N. Zwerdling, Enhancing cluster labeling using wikipedia, in: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development Information Retrieval, 2009, pp. 139-146.
9. C.L. Chen, S. Frank, C. Tseng, and T. Liang An integration of fuzzy association rules and WordNet for document clustering Lecture Notes in Computer Science in Advances in Knowledge Discovery and Data Mining 2009 147 159
10. W.H.E. Day, and H. Edelsbrunner Efficient algorithms for agglomerative hierarchical clustering methods Journal of Classification 1984 7 24
11. A. El-Hamdouchi, and P. Willett Comparison of hierarchic agglomerative clustering methods for document retrieval The Computer Journal 32 1989 220 227
12. T.F. Gharib, M.M. Fouad, and M.M. Aref Fuzzy document clustering approach using WordNet lexical categories Khaled Elleithy, Advanced Techniques in Computing Sciences and Software Engineering 2010 Springer Science+Business, Media B.V. 181 ISBN 978-90-481-3659-9
13. M. Hoon, S. Imoto, and S. Miyano The C Clustering Library 2003 Institute of Medical Science, Human Genome Center University of Tokyo
14. G. Karypis, {CLUTO} a clustering toolkit, Technical Report 02-017, Dept. of Computer Science, University of Minnesota, 2002. < http://www.cs.umn. edu~cluto >.
15. G.V.R. Kiran, R. Shankar, V. Pudi, Frequent itemset based hierarchical document clustering using Wikipedia as external knowledge, in: KES'10 Proceedings of the 14th International Conference on Knowledge-Based and Intelligent Information And Engineering Systems: Part II, 2010, pp. 11-20.
16. A. Purandare, T. Pedersen, SenseClusters - finding clusters that represent word senses. in: Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-04), San Jose, USA, 2004, pp. 25-29.
17. S. Rodpongpun, V. Niennattrakul, C.A. Ratanamahatana, Selective subsequence time series clustering, Knowledge Based Systems (2012), http://dx.doi.org/10.1016/j.knosys.2012.04.022.
18. G. Salton, A. Wong, and C.S. Yang A vector space model for automatic indexing Communications of the ACM 18 11 1975 613 620
19. J. Sedding, D. Kazakov, WordNet-based text document clustering, in: Proceedings of COLING-Workshop on Robust Methods in Analysis of Natural Language Data, 2004.
20. M. Steinbach, G. Karypis, V. Kumar, A comparison of document clustering techniques, Department of Computer Science and Engineering, University of Minnesota, 2000.
21. J. Taeho, and L. Malrey The evaluation measure of text clustering for the variable number of clusters Advances in Neural Networks 4492 2007 871 879 ISNN 2007
22. P. Treeratpituk, J. Callan, Automatically labeling hierarchical clusters, in: Proceedings of the 2006 International Conference on Digital Government Research, San Diego, California, 2006 May 21-24.
23. Y.H. Tseng Generic title labeling for clustered documents. Expert Systems with Applications 37 3 2009 2247 2254 (Elsevier)
24. G. Varelas, E. Voutsakis, P. Raftopoulou, E. Petrakis, E. Milios, Semantic similarity methods in wordNet and their application to information retrieval on the web, in: Workshop on Web Information and Data Management, Proceedings of the 7th Annual ACM International Workshop on Web Information and Data Management, 2005, pp. 10-16.
25. L. Yanjun, and C. Soon Parallel bisecting k-means with prediction clustering algorithm The Journal of Supercomputing 39 2007 19 37
26. Y. Zhao, and G. Karypi Empirical and theoretical comparisons of selected criterion functions for document clustering Machine Learning 55 3 2004 311 331