標題: Titlebook: Recommender Systems Handbook; Francesco Ricci,Lior Rokach,Bracha Shapira Book 20152nd edition Springer Science+Business Media New York 201 [打印本頁] 作者: 使沮喪 時間: 2025-3-21 17:12
書目名稱Recommender Systems Handbook影響因子(影響力)
書目名稱Recommender Systems Handbook影響因子(影響力)學科排名
書目名稱Recommender Systems Handbook網絡公開度
書目名稱Recommender Systems Handbook網絡公開度學科排名
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讀者反饋學科排名
作者: semble 時間: 2025-3-21 21:03 作者: Explicate 時間: 2025-3-22 01:20
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.作者: Venules 時間: 2025-3-22 05:57
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.作者: cauda-equina 時間: 2025-3-22 11:25
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.作者: 濕潤 時間: 2025-3-22 15:33 作者: 業(yè)余愛好者 時間: 2025-3-22 19:22
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.作者: 要素 時間: 2025-3-23 00:29 作者: Mutter 時間: 2025-3-23 02:23
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作者: Chemotherapy 時間: 2025-3-23 05:55
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.作者: Arrhythmia 時間: 2025-3-23 10:45 作者: CHAR 時間: 2025-3-23 15:01
Recommender Systems: Introduction and Challenges,In this introductory chapter, we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook. Additionally, we aim to help the reader navigate the rich and detailed content that this handbook offers.作者: superfluous 時間: 2025-3-23 21:53
A Comprehensive Survey of Neighborhood-Based Recommendation Methodseir efficiency, and their ability to produce accurate and personalized recommendations. This chapter presents a comprehensive survey of neighborhood-based methods for the item recommendation problem. In particular, the main benefits of such methods, as well as their principal characteristics, are de作者: Lipoprotein 時間: 2025-3-24 02:02
Advances in Collaborative Filteringin the recently completed Netflix competition has contributed to its popularity. This chapter surveys the recent progress in the field. Matrix factorization techniques, which became a first choice for implementing CF, are described together with recent innovations. We also describe several extension作者: 構成 時間: 2025-3-24 05:45
Semantics-Aware Content-Based Recommender Systemsectively exploited to suggest items similar to those a target user already liked in the past. Most content-based recommender systems use textual features to represent items and user profiles, hence they suffer from the classical problems of natural language ambiguity. This chapter presents a compreh作者: 不可知論 時間: 2025-3-24 07:18 作者: 本土 時間: 2025-3-24 12:29
Context-Aware Recommender Systemsn, information retrieval, ubiquitous and mobile computing, data mining, marketing, and management. While a substantial amount of research has already been performed in the area of recommender systems, many existing approaches focus on recommending the most relevant items to users without taking into作者: grieve 時間: 2025-3-24 16:34 作者: 聽覺 時間: 2025-3-24 20:39
Evaluating Recommender Systemsses a system designer that wishes to employ a recommendater system must choose between a set of candidate approaches. A first step towards selecting an appropriate algorithm is to decide which properties of the application to focus upon when making this choice. Indeed, recommender systems have a var作者: badinage 時間: 2025-3-24 23:44 作者: 仔細閱讀 時間: 2025-3-25 04:16
Explaining Recommendations: Design and Evaluatione are interested in what makes an explanation “good”. The chapter starts by describing how explanations can be affected by how recommendations are presented, and the role the interaction with the recommender system plays w.r.t. explanations. Next, we introduce a number of explanation styles, and how作者: 節(jié)約 時間: 2025-3-25 11:17
Recommender Systems in Industry: A Netflix Case Studyons about how to approach recommendation and many more have been learned since the Grand Prize was awarded in 2009. The evolution of industrial applications of recommender systems has been driven by the availability of different kinds of user data and the level of interest for the area within the re作者: occurrence 時間: 2025-3-25 14:41 作者: Constant 時間: 2025-3-25 17:27
Music Recommender Systemskinds of media. We then provide a literature survey of content-based music recommendation, contextual music recommendation, hybrid methods, and sequential music recommendation, followed by overview of evaluation strategies and commonly used data sets. We conclude by pointing to the most important ch作者: 高原 時間: 2025-3-25 20:37 作者: 拱形大橋 時間: 2025-3-26 00:53
Social Recommender Systemsered by recommendations and those sites rely on the quality of the recommendations to attract new users and retain existing ones. In this chapter, we introduce the notion of social recommender systems as recommender systems that target the social media domain. After a short introduction, we discuss 作者: 無情 時間: 2025-3-26 05:22
People-to-People Reciprocal Recommendersey must satisfy the preferences and needs of the two parties involved in the recommendation. In contrast, traditional items-to-people recommenders are one-sided and must satisfy only the preference of the person for whom the recommendation is generated. We review the characteristics and present an o作者: faultfinder 時間: 2025-3-26 10:49 作者: 檢查 時間: 2025-3-26 13:31 作者: legislate 時間: 2025-3-26 18:23 作者: Stable-Angina 時間: 2025-3-27 00:35
Music Recommender Systemskinds of media. We then provide a literature survey of content-based music recommendation, contextual music recommendation, hybrid methods, and sequential music recommendation, followed by overview of evaluation strategies and commonly used data sets. We conclude by pointing to the most important challenges faced by music recommendation research.作者: fleeting 時間: 2025-3-27 01:42 作者: 四指套 時間: 2025-3-27 05:19 作者: Customary 時間: 2025-3-27 09:52
Lisbon Treaty, is said to be notoriously undertheorised. The first wave of literature on the subject resembles diplomatic history, being based on journalistic accounts of key events. It tends to cite official documents about institutional development, together with anecdotal, politically loaded or o作者: ABIDE 時間: 2025-3-27 15:26
Xia Ning,Christian Desrosiers,George Karypis, we both agreed on certain fundamental points. (1) Both of us rejected the doctrine, enunciated by Gilbert Harman [Harman 1965], that . forms of nondemonstrative inference fall under the rubric of Inference to the Best Explanation. (2) We agreed that the Hypothetico-Deductive method is fatally flaw作者: 迅速成長 時間: 2025-3-27 21:45
Yehuda Koren,Robert Bell, we both agreed on certain fundamental points. (1) Both of us rejected the doctrine, enunciated by Gilbert Harman [Harman 1965], that . forms of nondemonstrative inference fall under the rubric of Inference to the Best Explanation. (2) We agreed that the Hypothetico-Deductive method is fatally flaw作者: Audiometry 時間: 2025-3-28 01:16
Marco de Gemmis,Pasquale Lops,Cataldo Musto,Fedelucio Narducci,Giovanni Semeraro, we both agreed on certain fundamental points. (1) Both of us rejected the doctrine, enunciated by Gilbert Harman [Harman 1965], that . forms of nondemonstrative inference fall under the rubric of Inference to the Best Explanation. (2) We agreed that the Hypothetico-Deductive method is fatally flaw作者: perimenopause 時間: 2025-3-28 04:28
Alexander Felfernig,Gerhard Friedrich,Dietmar Jannach,Markus Zanker, we both agreed on certain fundamental points. (1) Both of us rejected the doctrine, enunciated by Gilbert Harman [Harman 1965], that . forms of nondemonstrative inference fall under the rubric of Inference to the Best Explanation. (2) We agreed that the Hypothetico-Deductive method is fatally flaw作者: Crohns-disease 時間: 2025-3-28 08:25 作者: 責難 時間: 2025-3-28 11:01
Xavier Amatriain,Josep M. Pujol merely sentential instruments for the deductive integration and prediction of observational regularity. The instrumentalists Osiander and Ursus protected Copernicus’s theory from church antogonism (since the Catholic church was committed to the Ptolemeic theory as church dogma) by arguing that the 作者: 撫慰 時間: 2025-3-28 15:27
Hendrik Drachsler,Katrien Verbert,Olga C. Santos,Nikos Manouselis作者: 外向者 時間: 2025-3-28 21:40 作者: 道學氣 時間: 2025-3-28 23:58 作者: Arb853 時間: 2025-3-29 03:36 作者: 相互影響 時間: 2025-3-29 10:59 作者: 充足 時間: 2025-3-29 12:58
Context-Aware Recommender Systems three popular algorithmic paradigms—contextual pre-filtering, post-filtering, and modeling—for incorporating contextual information into the recommendation process, and survey recent work on context-aware recommender systems. We also discuss important directions for future research.作者: colony 時間: 2025-3-29 17:47 作者: BAN 時間: 2025-3-29 21:43
People-to-People Reciprocal Recommenderst and explicit user preferences and show that implicit preferences, learned from user interactions, are better predictors of successful interactions. We conclude by outlining some future research directions.作者: 澄清 時間: 2025-3-30 03:56
Book 20152nd editionser interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender system作者: cinder 時間: 2025-3-30 04:14
eorisation. It brings together scholars in the field who map their respective theoretical apparatuses, reflect on their purchase and illustrate how they have informed their empirical explorations. Diversity of theoretical assumptions has pervaded the literature on the subject from the outset. The av作者: 精密 時間: 2025-3-30 09:59 作者: botany 時間: 2025-3-30 15:27 作者: Recess 時間: 2025-3-30 18:24
