This thesis is only concerned with text clustering. That is, it makes no priori assumptions about the interrelationships of Hardy’s prose works.
Computational methods of text clustering fall into two main categories. These are linguistic and statistical mathematical methods (Srivastava and Sahami, 2009; Justo and Torres, 2005). Linguistic methods are based on natural language processing techniques. Methods of this kind usually involve morphological and syntactic processes for extracting meaning and identifying relationships within documents. Mathematical and statistical classificatio...
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...sks including SenseClusters (Purandare and Pedersen, 2004). This and others are programs that allow users to cluster similar contexts such as emails and web pages (Pedersen, 2008). The working principle of such programs is that data documents can be grouped on the basis of their mutual contextual similarities (Purandare and Pedersen, 2004). Programs of this kind have indeed proven a successful clustering method when applied to web pages and its merits are more tangible with multimedia material. Nevertheless, an approach of this kind carries with it some limitations. One of them- perhaps the most important- is that it is not concerned with the analysis of the content of documents. One more drawback is that in almost all context classification applications “identical replications of controlled experiments result in different conclusions” (Martin et al., 2005: 470).
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