Document Clustering Using Semantic Cliques Aggregation
نویسندگان
چکیده
منابع مشابه
Document Clustering Using Semantic Cliques Aggregation
The search engines are indispensable tools to find information amidst massive web pages and documents. A good search engine needs to retrieve information not only in a shorter time, but also relevant to the users’ queries. Most search engines provide short time retrieval to user queries; however, they provide a little guarantee of precision even to the highly detailed users’ queries. In such ca...
متن کاملUsing 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...
متن کاملEnhancing Document Clustering Using Hybrid Models for Semantic Similarity
Different document representation models have been proposed to measure semantic similarity between documents using corpus statistics. Some of these models explicitly estimate semantic similarity based on measures of correlations between terms, while others apply dimension reduction techniques to obtain latent representation of concepts. This paper proposes new hybrid models that combine explici...
متن کاملA Semantic approach for effective document clustering using WordNet
— Now a days, the text document is spontaneously increasing over the internet, e-mail and web pages and they are stored in the electronic database format. To arrange and browse the document it becomes difficult. To overcome such problem the document preprocessing, term selection, attribute reduction and maintaining the relationship between the important terms using background knowledge, WordNet...
متن کاملUsing a Wikipedia-based Semantic Relatedness Measure for Document Clustering
A graph-based distance between Wikipedia articles is defined using a random walk model, which estimates visiting probability (VP) between articles using two types of links: hyperlinks and lexical similarity relations. The VP to and from a set of articles is then computed, and approximations are proposed to make tractable the computation of semantic relatedness between every two texts in a large...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computer and Communications
سال: 2015
ISSN: 2327-5219,2327-5227
DOI: 10.4236/jcc.2015.312004