Survey on Semantic Similarity Based on Document Clustering

Word Semantic Similarity based on document title

An improved semantic similarity measure for document clustering based on topic maps

A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assigns a real number between 0 and 1 to a pair of documents, depending upon the degree of similarity between them. A value of zero means that the documents are completely dissimilar whereas a value of one indicates that ...

Experiments on Semantic-based Clustering for Cross-document Coreference

We describe clustering experiments for cross-document coreference for the first Web People Search Evaluation. In our experiments we apply agglomerative clustering to group together documents potentially referring to the same individual. The algorithm is informed by the results of two different summarization strategies and an offthe-shelf named entity recognition component. We present different ...

Web Document Clustering based on Document Structure

Document clustering techniques mostly rely on single term analysis of the document data set, such as the Vector Space Model. To achieve more accurate document clustering, document structure should be reflected in the underlying data model. This paper presents a framework for web document clustering based on two important concepts. The first one is the web document structure, which is currently ...

Using Fuzzy Logic Clustering Discover Semantic Similarity in Web Document

The complex and high interactions between terms in documents demonstrates vague and ambiguous meanings. There exist complicated associations within one web document and linking to the others. Most of these approaches perform similarity and feature section methods. There is need of complex document clustering and produced meaningful document. This paper proposed methodology is capable of handles...