Visual Data Mining for Collaborative Filtering: A State-of-the-Art Survey

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Author(s): Marenglen Biba (University of New York Tirana, Albania), Narasimha Rao Vajjhala (University of New York Tirana, Albania)and Lediona Nishani (University of New York Tirana, Albania)
Copyright: 2017
Pages: 19
Source title: Decision Management: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1837-2.ch059

Keywords: Business & Management / Decision Support Systems / Information Science Reference

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Abstract

This book chapter provides a state-of-the-art survey of visual data mining techniques used for collaborative filtering. The chapter begins with a discussion on various visual data mining techniques along with an analysis of the state-of-the-art visual data mining techniques used by researchers as well as in the industry. Collaborative filtering approaches are presented along with an analysis of the state-of-the-art collaborative filtering approaches currently in use in the industry. Visual data mining can provide benefit to existing data mining techniques by providing the users with visual exploration and interpretation of data. The users can use these visual interpretations for further data mining. This chapter dealt with state-of-the-art visual data mining technologies that are currently in use apart. The chapter also includes the key section of the discussion on the latest trends in visual data mining for collaborative filtering.

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Visual Data Mining for Collaborative Filtering: A State-of-the-Art Survey

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