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This paper presents a system that combines two text mining techniques; information extraction and clustering. A rule-based approach is used to perform the information extraction task, based on the dependency relation between some intransitive verbs and prepositions. This relationship helps in extracting types of crime from documents within the crime domain. With regard to the clustering task, the...
As a kind of data model, a formal context must be extracted from some actual data sources such as documents. For case of unstructured Chinese document, it is the first question to decide how to express the document. Vector space model (VSM) which is the dominant model of document expression now takes a single word as a feature item, so that neglects the lexical semantic relationship between words...
This paper describes an initial prototype for identifying types of crime in a text within the crime domain. Two approaches are explored to perform recognition tasks. The first approach completely relies on direct recognition using gazetteers. In this case, lists of crime verbs and crime names are used. The second approach is a rule-based system. Rules are built based on the predefined crime indicator...
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