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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 becoming a sizzling hot topic under the aegis of Information Retrieval. In this paper,...
be easily extracted, building respective data banks. Keywords are the important terms, sometimes called, index terms that contain some kind of valuable information about the document. Automatic keyword extraction is the task to identify a small set of words, which can be designated as keywords for that document, and
effort, and would most likely be disruptive. In this paper, we describe ways to use the results of semantic analysis and disambiguation, while retaining an existing keyword-based search and lexicographic index. We engineer this so the output of semantic analysis (performed off-line) is suitable for import directly into
Traditional Web retrieval system is based on whole-length search of keyword, which would bring large results, but users can't find the answer that they need quickly. This paper presents a model of information retrieval based on media data, to improve the web information retrieval efficiency and precision in specific
search engine prototype backed by Supplejack, which has been loaded with sample metadata from a variety of organizations in Ontario and British Columbia with diverse metadata schema. Keywords--supplejack, digital library, search portal, ingest, metadata, ourdigitalworld, odw, british columbia library association, bcla
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.