Titlebook: Recommender Systems Handbook; Francesco Ricci,Lior Rokach,Bracha Shapira Book 20152nd edition Springer Science+Business Media New York 201

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書目名稱Recommender Systems Handbook影響因子(影響力)




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書目名稱Recommender Systems Handbook網(wǎng)絡(luò)公開(kāi)度




書目名稱Recommender Systems Handbook網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Recommender Systems Handbook被引頻次




書目名稱Recommender Systems Handbook被引頻次學(xué)科排名




書目名稱Recommender Systems Handbook年度引用




書目名稱Recommender Systems Handbook年度引用學(xué)科排名




書目名稱Recommender Systems Handbook讀者反饋




書目名稱Recommender Systems Handbook讀者反饋學(xué)科排名

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Explicate

The Anatomy of Mobile Location-Based Recommender Systemsrecommending venues, and the techniques that researchers have used to evaluate the quality of these recommendations, using research that is sourced from a variety of fields. This chapter closes by highlighting a number of opportunities and open challenges related to building future mobile recommender systems.

Venules

Advances in Collaborative Filterings that bring competitive accuracy into neighborhood methods, which used to dominate the field. The chapter demonstrates how to utilize temporal models and implicit feedback to extend models accuracy. In passing, we include detailed descriptions of some the central methods developed for tackling the challenge of the Netflix Prize competition.

cauda-equina

Evaluating Recommender Systems with User Experimentsments, covering the following topics: formulating hypotheses, sampling participants, creating experimental manipulations, measuring subjective constructs with questionnaires, and statistically evaluating the results.

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業(yè)余愛(ài)好者

Data Mining Methods for Recommender Systemsnd Support Vector Machines. We describe the .-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

要素

Mutter

Book 20152nd editiontheories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included.In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems

Chemotherapy

Recommender Systems in Industry: A Netflix Case Studyrom the Netflix Prize. We will then use Netflix personalization as a case study to describe several approaches and techniques used in a real-world recommendation system. Finally, we will pinpoint what we see as some promising current research avenues and unsolved problems that deserve attention in this domain from an industry perspective.