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Titlebook: Information Retrieval Architecture and Algorithms; Gerald Kowalski Textbook 2011 Springer Science+Business Media, LLC 2011 Clustering.Data

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Information Retrieval System Functions,etrieval systems along with the user’s functions is needed. This background helps in understanding some of the technical drivers on final implementation. To place Information Retrieval Systems into perspective, it’s also useful to discuss how they are the same and differ from other information handl
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Ingest,f the system. The selection of what to ingest into the system and elimination of duplicates can reduce extraneous items that produce hits the user is not interested in. The selection of sources to receive or the crawling rules (frequency, depth versus breath crawling) all effect what users will find
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Search, The search process uses the users query as a starting point in determining what items are most likely relevant to the user. This process revolves around a similarity measure formula that is used along with any heuristics added to improve the basic formula. There are many different similarity measur
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Information Presentation,al discussion on information visualization or presentation. The various scenarios of information presentation are defined along with aspects of their presentation. Visualization of search results is organized by linear lists, clustering views, network views and time line presentation. Collaborative
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