Abstract
Document clustering description is a problem of labeling the clustering results of document collection clustering. It can help users determine whether one of the clusters is relevant to their information requirements or not. To resolve the problem of the weak readability of document clustering results, a method of automatic labeling document clusters based on machine learning is put forward. Clustering description extraction in application to topic digital library construction is introduced firstly. Then, the descriptive results of five models are analyzed respectively, and their performances are compared.
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Zhang, C., Wang, H., Liu, Y., Xu, H. (2009). Document Clustering Description Extraction and Its Application. In: Li, W., Mollá-Aliod, D. (eds) Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy. ICCPOL 2009. Lecture Notes in Computer Science(), vol 5459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00831-3_37
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DOI: https://doi.org/10.1007/978-3-642-00831-3_37
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