2001 OntologyBasedTextClustering
- (Hotho et al., 2001) ⇒ Andreas Hotho, Alexander Maedche, Steffen Staab. (2001). “Ontology-based Text Clustering.” In: Proceedings of the IJCAI-2001 Workshop on Text Learning: Beyond Supervision.
Subject Headings: Text Clustering Algorithm, Document Vector, Word Vector.
Notes
- See their subsequent work (Hotho et al., 2003) ⇒ Andreas Hotho, Steffen Staab, and Gerd Stumme. (2003). “Wordnet Improves Text Document Clustering.” In: Proceedings of the SIGIR Workshop on Semantic Web Workshop.
Cited By
Quotes
Abstract
Text clustering typically involves clustering in a high dimensional space, which appears difficult with regard to virtually all practical settings. In addition, given a particular clustering result it is typically very hard to come up with a good explanation of why the text clusters have been constructed the way they are. In this paper, we propose a new approach for applying background knowledge during preprocessing in order to improve clustering results and allow for selection between results. We built various views basing our selection of text features on a heterarchy of concepts. Based on these aggregations, we compute multiple clustering results using K-Means. The results may be distinguished and explained by the corresponding selection of concepts in the ontology. Our results compare favourably with a sophisticated baseline preprocessing strategy.
References
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