Semantic Document Clustering Using Soft Computing Techniques
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Information retrieval technology has been central to the success of the web. The goal of information retrieval is to provide users with those documents that will satisfy their information need. With the large volume of data available in the web, retrieving relevant information becomes a difficult task. The common reason for this problem is that currently content-description and query-processing techniques for information retrieval are based on keywords. This involves limitations such as inability to describe semantic relations between search terms. Semantically-enhanced information retrieval o...
Information retrieval technology has been central to the success of the web. The goal of information retrieval is to provide users with those documents that will satisfy their information need. With the large volume of data available in the web, retrieving relevant information becomes a difficult task. The common reason for this problem is that currently content-description and query-processing techniques for information retrieval are based on keywords. This involves limitations such as inability to describe semantic relations between search terms. Semantically-enhanced information retrieval overcomes the limitations faced by keyword based search since the focus is on semantics leading to better and accurate results. Even for the use of semantic technology, efficient clustering techniques are needed to improve the relevancy of documents, and also optimization problem occurs, but is rarely considered. The main objective of Document-Clustering is to avoid the recovery of non-relevant documents.
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