Free BookRecommender Systems Handbook

[Ebook.NzKR] Recommender Systems Handbook

[Ebook.NzKR] Recommender Systems Handbook

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Book Details :
Published on: 2013-06-04
Released on: 2013-06-04
Original language:

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments.Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included.Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and ATT. This handbook is suitable for researchers and advanced-level students in computer science as a reference. Perceived usefulness perceived ease of use and user ... Author: Fred D. Davis: Computer and Information Systems Graduate School of Business Administration University of Michigan Ann Arbor ... An Overview of Data Warehousing and OLAP Technology Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support which has increasingly become a focus of the database industry. Computer Science Springer On these pages you will find Springers journals ebooks and proceedings in all areas of Computer Science serving researchers professionals lecturers and students. Cold start - Wikipedia Cold start is a potential problem in computer-based information systems which involve a degree of automated data modelling. Specifically it concerns the issue that ... Recommender system - Wikipedia Recommender systems or recommendation systems (sometimes replacing "system" with a synonym such as platform or engine) are a subclass of information filtering system ... Guerrilla Painter Easel Systems - Jerry's Artarama Guerrilla Painter Boxes are perfect for artists on the go. These oiled plywood boxes are sturdy yet beautiful and they can safely carry and protect up to two wet ... Publications & Standards - IEEE Browse IEEE publications and standards and visit the IEEE Xplore Digital Library. Link to IEEE Spectrum Magazine and The Institute member newsletter. Computer Science Stanford University Computer Science Course Catalog Numbering System; Digit Description; 00-09: Introductory miscellaneous: 10-19: Hardware and Software Systems: 20-39: Artificial ... Resolve a DOI Name Type or paste a DOI name into the text box. Click Go. Your browser will take you to a Web page (URL) associated with that DOI name. Send questions or comments to doi ... Collaborative Filtering Recommender Systems By ... - GroupLens 84 Introduction user experience data collection and other problems which make up the whole of the recommender experience. 1.1 History of Recommender Systems
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