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Such a domain image can be presented in the form of ontologies (Chen, 2006). RVDOD %ORFNHHO &DSWXULQJ the content of Web data in ontologies is the ¿UVWVWHSWRZDUGVWKHEXLOGLQJRI6HPDQWLF Web applications. Thus, natural language text is considered as the most important source data of ontologies for the Semantic Web (Maedche, 2003). Although techniques and tools for ontology construction have been developed over the last decade, they provide little support to EXLOGLQJRQWRORJLHVLQDQHI¿FLHQWHQJLQHHUing manner.
However, the design of a more appropriate context factor scale requires more efforts. An important issue with taking a hierarchical clustering approach is the need of pre-processing source data. Since existing clustering algorithms require input in numeric form, coding text and scaling them to numbers can result in the loss of semantics (“meaning”) in text. Therefore, careful pre-processing is essential. A common approach is to perform term extraction. , 2005). Another important issue is the post-processing of 22 resultant clusters, referred to as cluster labeling, a semantic problem.
PC Advisor (July 2012)
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