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The existing expert information systems supply services for searching information of experts and help the users to select suitable experts to evaluate all types of projects in different fields, however, almost all of these search services use keyword match, and it is hard to gain high search efficiency. Ontology has
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
Traditional Web Service search methodology dependant on keywords is time consuming and inefficient. The search results are often inexact. The substantive reason is that, the description of Web Service lacks semantic information. Search Engines can't accomplish the communication automatically and intelligently between
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.