Identifying Semantic in High-Dimensional Web Data Using Latent Semantic Manifold
نویسندگان
چکیده
منابع مشابه
Identifying Semantic in High-Dimensional Web Data Using Latent Semantic Manifold
Latent Semantic Analysis involves natural language processing techniques for analyzing relationships between a set of documents and the terms they contain, by producing a set of concepts (related to the documents and terms) called semantic topics. These semantic topics assist search engine users by providing leads to the more relevant document. We develope a novel algorithm called Latent Semant...
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To buy his/her necessities such as books, movies, CD, music, etc., one always trusts others’ oral and written consultations and offers and include them in his/her decisions. Nowadays, regarding the progress of technologies and development of e-business in websites, a new age of digital life has been commenced with the Recommender systems. The most important objectives of these systems include a...
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Search engines have become an indispensable tool for obtaining relevant information on the Web. The search engine often generates a large number of results, including several irrelevant items that obscure the comprehension of the generated results. Therefore, the search engines need to be enhanced to discover the latent semantics in high-dimensional web data. This paper purports to explain a no...
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ژورنال
عنوان ژورنال: Journal of Data Analysis and Information Processing
سال: 2015
ISSN: 2327-7211,2327-7203
DOI: 10.4236/jdaip.2015.34014