图书标签: 推荐系统 数据挖掘 recommender 机器学习 recsys 算法 计算机 互联网
发表于2024-12-23
Recommender Systems Handbook pdf epub mobi txt 电子书 下载 2024
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 AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.
Paul Kantor, Rutgers University, School of Communication, USA
Francesco Ricci, Free University of Bozen-Bolzano, Faculty of Computer Science, Italy
Lior Rokach, Information System Engineering, Ben-Gurion University, Israel
Bracha Shapira, Information System Engineering, Ben-Gurion University, Israel
不是太好,糙
评分经典枕头书。不过不是从业者,理解起来还是困难。
评分经典枕头书。不过不是从业者,理解起来还是困难。
评分这本书把推荐系统说的很全面
评分去年陆续翻了一些章节。全面、粗浅。但篇幅巨大,不适合入门。作为特定问题的资料索引,应该不错。
专题性质的, 从推荐引擎中数据预处理, 基本挖掘算法, 各种推荐方式, 到用户界面对用户采用的影响都有涉及。 对于一个想将推荐作为方向做下去的人, 必须要看该书。 每个专题都会列出专题涉及到的论文及将来的发展趋势, 具有很好的指导作用
评分专题性质的, 从推荐引擎中数据预处理, 基本挖掘算法, 各种推荐方式, 到用户界面对用户采用的影响都有涉及。 对于一个想将推荐作为方向做下去的人, 必须要看该书。 每个专题都会列出专题涉及到的论文及将来的发展趋势, 具有很好的指导作用
评分Preface Contents Contributors 1 Recommender Systems: Introduction and Challenges 1.1 Introduction 1.2 Recommender Systems' Function 1.3 Data and Knowledge Sources 1.4 Recommendation Techniques 1.5 Recommender Systems Evaluation 1.6 Recommender Systems Appli...
评分Preface Contents Contributors 1 Recommender Systems: Introduction and Challenges 1.1 Introduction 1.2 Recommender Systems' Function 1.3 Data and Knowledge Sources 1.4 Recommendation Techniques 1.5 Recommender Systems Evaluation 1.6 Recommender Systems Appli...
评分Preface Contents Contributors 1 Recommender Systems: Introduction and Challenges 1.1 Introduction 1.2 Recommender Systems' Function 1.3 Data and Knowledge Sources 1.4 Recommendation Techniques 1.5 Recommender Systems Evaluation 1.6 Recommender Systems Appli...
Recommender Systems Handbook pdf epub mobi txt 电子书 下载 2024