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Online searching of books have gained astounding popularity worldwide. It has also attracted variety of researchers globally. Searching of books (e.g. Amazon.com, aNobii, LibraryThing etc) with the help of Social metadata(e.g. tags, reviews) and professional metadata (e.g. ISBN Number, Title, Publisher) is gradually
interest areas coinciding with the related book categories. This paper suggests that bloggerspsila interests can be known through extracting keywords from blog entry titles and using book classification schemes. Because there were instances in which the keywords alone did not provide adequate information, the Naver (Korean
XML is an extremely nifty format. Computers can easily parse XML data, yet humans can also understand it. By adopting XML, we can take advantage of the scores of tools that work on arbitrary XML documents. Common tasks like editing, validation, transformations, and queries become just a matter of selecting and
outputs during 2002-2008, distribution of source title, author keywords, and keyword plus analysis. The exponential fitting of the yearly publications of the last decade can also calculate that, in 2014, the number of scientific papers on innovation will be twice the number of publications in 2008. Synthetically analyzing
Expert finding would be useful for a recommendation system which people want to find experts in a specific area. This paper proposes a model to identify focus research areas of computer science researchers thru their publications. We collect title, abstract and keywords of academic papers published in IEEE Xplore
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