Abstract
In this paper, we introduce BorderFlow, a novel local graph clustering algorithm, and its application to natural language processing problems. For this purpose, we first present a formal description of the algorithm. Then, we use BorderFlow to cluster large graphs and to extract concepts from word similarity graphs. The clustering of large graphs is carried out on graphs extracted from the Wikipedia Category Graph. The subsequent low-bias extraction of concepts is carried out on two data sets consisting of noisy and clean data. We show that BorderFlow efficiently computes clusters of high quality and purity. Therefore, BorderFlow can be integrated in several other natural language processing applications.
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References
Ananiadou, S., Mcnaught, J.: Text Mining for Biology and Biomedecine, Norwood, MA, USA (2005)
Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley (1999)
Biemann, C.: Chinese whispers - an efficient graph clustering algorithm and its application to natural language processing problems. In: Proceedings of the HLT-NAACL 2006 Workshop on Textgraphs, New York, USA (2006)
Fernández-López, M., Gómez-Pérez, A.: Overview and analysis of methodologies for building ontologies. Knowledge Engineering Review 17(2), 129–156 (2002)
Flake, G., Lawrence, S., Giles, C.L.: Efficient identification of web communities. In: Proceedings of the 6th ACM SIGKDD, Boston, MA, pp. 150–160 (2000)
Heyer, G., Luter, M., Quasthoff, U., Wittig, T., Wolff, C.: Learning relations using collocations. In: Workshop on Ontology Learning. CEUR Workshop Proceedings, vol. 38, CEUR-WS.org. (2001)
Jacquemin, C., Klavans, J., Tzoukermann, E.: Expansion of multi-word terms for indexing and retrieval using morphology and syntax. In: Proceeding of ACL-35, pp. 24–31 (1997)
Maguitman, A., Leake, D., Reichherzer, T., Menczer, F.: Dynamic extraction topic descriptors and discriminators: towards automatic context-based topic search. In: Proceedings of the Thirteenth ACM International Conference on Information and Knowledge Management, pp. 463–472. ACM, New York (2004)
Ngonga Ngomo, A.-C.: SIGNUM: A graph algorithm for terminology extraction. In: Gelbukh, A. (ed.) CICLing 2008. LNCS, vol. 4919, pp. 85–95. Springer, Heidelberg (2008)
Robertson, S.E., Hull, D.: The TREC 2001 filtering track report. In: Proceedings of the Text REtrieval Conference (2001)
Rousseeuw, P.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics 20(1), 53–65 (1987)
Schütze, H.: Automatic word sense discrimination. Computational Linguistics 24(1), 97–123 (1998)
Shannon, C.E.: A mathematic theory of communication. Bell System Technical Journal 27, 379–423 (1948)
van Dongen, S.: Graph Clustering by Flow Simulation. PhD thesis, University of Utrecht (2000)
Zesch, T., Gurevych, I.: Analysis of the Wikipedia Category Graph for NLP Applications. In: Proceedings of the NAACL-HLT 2007 Workshop on TextGraphs, pp. 1–8 (2007)
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Ngonga Ngomo, AC., Schumacher, F. (2009). BorderFlow: A Local Graph Clustering Algorithm for Natural Language Processing. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2009. Lecture Notes in Computer Science, vol 5449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00382-0_44
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DOI: https://doi.org/10.1007/978-3-642-00382-0_44
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