A more detailed discussion of the benets of this

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Unformatted text preview: hest relative entropy as an index term. Then mark again this document and all other documents containing this term. Repeat this process until all documents are marked, then unmark them all and start again. The process can be terminated when the desired number of index terms have been selected. A more detailed discussion of the benefits of this approach for clustering – with respect to reduction of words required in order to obtain a good clustering performance – can be found in Borgelt & Nürnberger (2004). An index term selection methods that is more appropriate if we have to learn a classifier for documents is discussed in Sect. 3.1.1. This approach also considers the word distributions within the classes. 2.2 The Vector Space Model Despite of its simple data structure without using any explicit semantic information, the vector space model enables very efficient analysis of huge document collections. It was originally introduced for indexing and information retrieval (Salt...
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