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Keyword-based search in general is particularly applicable if the searcher really knows what she is looking for and how to find it. But in many cases either the objectives of the searcher are intrinsically fuzzy or she has no idea of the appropriate keywords. One way to solve this problem is to navigate and explore
Due to the explosive growth of the amount of Web information, the effectiveness of keyword-based searching methods appears to reach a limit. One major reason is that the mixture of content and presentation information hinders machines in understanding the context of Web information and as a result, the performance of
A Max-Probability Density based Clustering (MPDC) algorithm is proposed in this paper to resolve the problem of Word Sense Disambiguation in semantic document. MPDC take the context information of a keyword based on WordNet into account and select the max probability sense by measuring the density of the concept. We
) information content due to occurrence of a property with respect to all the properties in a description base ii) unpredictability of an association due to participation of its properties in multiple domains iii) the extent of match between user specified keywords and properties and iv) the popularity of nodes involved in a
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