Abstract
This contribution describes clustering of most informative keywords within full-text query results and its visualization in 2D or 3D space using so-called sociomapping. The main goal of the clustering is to help user with orientation in the term space and with the reformulating – more detail specification – of ambiguous queries. Test data were obtained from web search engines like Yahoo!, Google etc. To be able to evaluate quality of the used clustering method we have used 2 metrics to compare it with manually classified collection (Reuters Corpus Volume 1), moreover, the quality of preserving mutual distances of clusters from original multi-dimensional space was measured by Spearman’s rank correlation coefficient.
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References
Liu, Y., Zhang, B., Chen, Z., Lyu, M.R., Ma, W.-Y.: Affinity Rank: A New Scheme for Efficient Web Search. In: WWW 2004, May 17–22. ACM, New York (2004), 1-58113-912-8/04/0005
Jenček, P., Höschl, C., Hudeček, J., Šebesta, J.: Mail Archiver Project, Software project documentation. Charles University, Prague (2009)
Höschl, C.: Sociomaps Visualisation, bachelor thesis, Charles University, Prague (in czech language) (2006), http://www.hoschl.cz/cyril/bakalarka/errata.pdf
Salton, G., Buckley, C.: Term weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)
MacQueen, J.B.: Some Methods for classification and Analysis of Multivariate Observations. In: Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)
Wang, D., Yu, G., Bao, Y., Zhang, M.: An Optimized K-Means Algorithm of Reducing Cluster Intra-dissimilarity for Document of Clustering Advances. In: Fan, W., Wu, Z., Yang, J. (eds.) WAIM 2005. LNCS, vol. 3739, pp. 785–790. Springer, Heidelberg (2005)
Dunn, J.C.: A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters. Journal of Cybernetics 3, 32–57 (1973)
Bahbouh, R., Warrenfeltz, R.: The Application of Sociomapping to Executive Team Development, http://www.hoganassessments.com/_hoganweb/documents/ApplicationOfSociomapping.pdf
Spearman, C.: The proof and measurement of association between two things. Amer. J. Psychol. 15, 72–101 (1904)
Borg, I., Groenen, P.: Modern Multidimensional Scaling: theory and applications, 2nd edn. Springer, New York (2005)
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Jenček, P., Vojtáš, P., Kopecký, M., Hösch, C. (2009). Sociomapping in Text Retrieval Systems. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_11
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DOI: https://doi.org/10.1007/978-3-642-04957-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04956-9
Online ISBN: 978-3-642-04957-6
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