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Measuring semantic similarity between two concepts is an important problem in web mining, targeted advertisement and domains that need semantic content matching. Nevertheless, developing a computational method capable of generating satisfactory results close to what humans would perceive is still a difficult task somewhat owed to the subjective nature of similarity. This paper presents an effective...
Information Content (IC) is an important dimension of assessing the semantic similarity between two terms or word senses in word knowledge. The conventional method of obtaining IC of word senses is to combine knowledge of their hierarchical structure from an ontology like WordNet with actual usage in text as derived from a large corpus. In this paper, a new model of IC is presented, which relies on...
Local context analysis is a main way to enhance the effectiveness of query expansion in the information retrieval field. A typical query may go through a pre- refinement process to improve its retrieval power. Most of the existing local context analysis methods are attempting to solve invalid selection of additive terms, which will result in retrieval performance degradation, in the process of query...
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