Personalization Techniques And Recommender Systems

Author : Gulden Uchyigit,Matthew Y. Ma
Publisher : World Scientific
Page : 334 pages
File Size : 41,7 Mb
Release : 2008
Category : Science
ISBN : 9789812797018

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Personalization Techniques and Recommender Systems by Gulden Uchyigit,Matthew Y. Ma Pdf

The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed.The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems.This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.

Author : Matthew Y. Ma,Gulden Uchyigit
Publisher : World Scientific
Page : 334 pages
File Size : 43,9 Mb
Release : 2008
Category : Computers
ISBN : 9789812797025

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Personalization Techniques and Recommender Systems by Matthew Y. Ma,Gulden Uchyigit Pdf

The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed. The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems. This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems. Sample Chapter(s). Personalization-Privacy Tradeoffs in Adaptive Information Access (865 KB). Contents: User Modeling and Profiling: Personalization-Privacy Tradeoffs in Adaptive Information Access (B Smyth); A Deep Evaluation of Two Cognitive User Models for Personalized Search (F Gasparetti & A Micarelli); Unobtrusive User Modeling for Adaptive Hypermedia (H J Holz et al.); User Modelling Sharing for Adaptive e-Learning and Intelligent Help (K Kabassi et al.); Collaborative Filtering: Experimental Analysis of Multiattribute Utility Collaborative Filtering on a Synthetic Data Set (N Manouselis & C Costopoulou); Efficient Collaborative Filtering in Content-Addressable Spaces (S Berkovsky et al.); Identifying and Analyzing User Model Information from Collaborative Filtering Datasets (J Griffith et al.); Content-Based Systems, Hybrid Systems and Machine Learning Methods: Personalization Strategies and Semantic Reasoning: Working in Tandem in Advanced Recommender Systems (Y Blanco-Fernindez et al.); Content Classification and Recommendation Techniques for Viewing Electronic Programming Guide on a Portable Device (J Zhu et al.); User Acceptance of Knowledge-Based Recommenders (A Felfernig et al.); Using Restricted Random Walks for Library Recommendations and Knowledge Space Exploration (M Franke & A Geyer-Schulz); An Experimental Study of Feature Selection Methods for Text Classification (G Uchyigit & K Clark). Readership: Researchers and graduate students in machine learning and databases/information science.

Author : Bamshad Mobasher,Sarabjot Singh Anand
Publisher : Springer Science & Business Media
Page : 332 pages
File Size : 52,9 Mb
Release : 2005-11-04
Category : Computers
ISBN : 9783540298465

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Intelligent Techniques for Web Personalization by Bamshad Mobasher,Sarabjot Singh Anand Pdf

This book constitutes the thoroughly refereed post-proceedings of the Second Workshop on Intelligent Techniques in Web Personalization, ITWP 2003, held in Acapulco, Mexico in August 2003 as part of IJCAI 2003, the 18th International Joint Conference on Artificial Intelligence. The 17 revised full papers presented were carefully selected and include extended versions of some of the papers presented at the ITWP 2003 workshop as well as a number of invited chapters by leading researchers in the field of Intelligent Techniques for Web Personalization. The papers are organized in topical sections on user modelling, recommender systems, enabling technologies, personalized information access, and systems and applications.

Author : Dehuri, Satchidananda
Publisher : IGI Global
Page : 351 pages
File Size : 50,6 Mb
Release : 2012-11-30
Category : Computers
ISBN : 9781466625433

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Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods by Dehuri, Satchidananda Pdf

Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.

Author : Francesco Ricci,Lior Rokach,Bracha Shapira
Publisher : Springer Nature
Page : 1053 pages
File Size : 42,9 Mb
Release : 2022-04-21
Category : Computers
ISBN : 9781071621974

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Recommender Systems Handbook by Francesco Ricci,Lior Rokach,Bracha Shapira Pdf

This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.

Author : Peter Brusilovski,Alfred Kobsa,Wolfgang Nejdl
Publisher : Springer Science & Business Media
Page : 770 pages
File Size : 43,6 Mb
Release : 2007-04-24
Category : Computers
ISBN : 9783540720782

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The Adaptive Web by Peter Brusilovski,Alfred Kobsa,Wolfgang Nejdl Pdf

This state-of-the-art survey provides a systematic overview of the ideas and techniques of the adaptive Web and serves as a central source of information for researchers, practitioners, and students. The volume constitutes a comprehensive and carefully planned collection of chapters that map out the most important areas of the adaptive Web, each solicited from the experts and leaders in the field.

Author : Gonz lez, Rafael Andr‚s,Chen, Nong,Dahanayake, Ajantha
Publisher : IGI Global
Page : 370 pages
File Size : 54,8 Mb
Release : 2008-03-31
Category : Computers
ISBN : 9781599045122

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Personalized Information Retrieval and Access: Concepts, Methods and Practices by Gonz lez, Rafael Andr‚s,Chen, Nong,Dahanayake, Ajantha Pdf

Global information retrieval and anywhere, anytime information access has stimulated a need to design and model the personalized information search in a flexible and agile way that can use the specific personalization techniques, algorithms, and available technology infrastructure to satisfy high-level functional requirements for personalization. Personalized Information Retrieval and Access: Concepts, Methods and Practices surveys the main concepts, methods, and practices of personalized information retrieval and access in today's data intensive, dynamic, and distributed environment, and provides students, researchers, and practitioners with authoritative coverage of recent technological advances that are shaping the future of globally distributed information retrieval and anywhere, anytime information access.

Author : Mrs. Nanda devi D.R
Publisher : Archers & Elevators Publishing House
Page : 71 pages
File Size : 42,5 Mb
Release : 2024-06-29
Category : Antiques & Collectibles
ISBN : 9788119385423

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Personalized Pathways: Job and Movie Recommendation Systems Unveiled by Mrs. Nanda devi D.R Pdf

Author : Marko Tkalčič,Berardina De Carolis,Marco de Gemmis,Ante Odić,Andrej Košir
Publisher : Springer
Page : 400 pages
File Size : 52,5 Mb
Release : 2016-07-13
Category : Computers
ISBN : 9783319314136

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Emotions and Personality in Personalized Services by Marko Tkalčič,Berardina De Carolis,Marco de Gemmis,Ante Odić,Andrej Košir Pdf

Personalization is ubiquitous from search engines to online-shopping websites helping us find content more efficiently and this book focuses on the key developments that are shaping our daily online experiences. With advances in the detection of end users’ emotions, personality, sentiment and social signals, researchers and practitioners now have the tools to build a new generation of personalized systems that will really understand the user’s state and deliver the right content. With leading experts from a vast array of domains from user modeling, mobile sensing and information retrieval to artificial intelligence, human-computer interaction (HCI) social computing and psychology, a broad spectrum of topics are covered. From discussing psychological theoretical models and exploring state-of-the-art methods for acquiring emotions and personality in an unobtrusive way, as well as describing how these concepts can be used to improve various aspects of the personalization process and chapters that discuss evaluation and privacy issues. Emotions and Personality in Personalized Systems will help aid researchers and practitioners develop and evaluate user-centric personalization systems that take into account the factors that have a tremendous impact on our decision-making – emotions and personality.

Author : Francesco Ricci,Lior Rokach,Bracha Shapira
Publisher : Springer
Page : 1003 pages
File Size : 40,6 Mb
Release : 2015-11-17
Category : Computers
ISBN : 9781489976376

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Recommender Systems Handbook by Francesco Ricci,Lior Rokach,Bracha Shapira Pdf

This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, 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, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user 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 systems.

Author : Aleksandra Klašnja-Milićević,Boban Vesin,Mirjana Ivanović,Zoran Budimac,Lakhmi C. Jain
Publisher : Springer
Page : 294 pages
File Size : 49,8 Mb
Release : 2016-07-19
Category : Technology & Engineering
ISBN : 9783319411637

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E-Learning Systems by Aleksandra Klašnja-Milićević,Boban Vesin,Mirjana Ivanović,Zoran Budimac,Lakhmi C. Jain Pdf

This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques.

Author : Julian McAuley
Publisher : Cambridge University Press
Page : 337 pages
File Size : 42,5 Mb
Release : 2022-02-03
Category : Computers
ISBN : 9781316518908

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Personalized Machine Learning by Julian McAuley Pdf

Explains methods behind machine learning systems to personalize predictions to individual users, from recommendation to dating and fashion.

Author : Zheng Xiang,Matthias Fuchs,Ulrike Gretzel,Wolfram Höpken
Publisher : Springer Nature
Page : 1976 pages
File Size : 44,7 Mb
Release : 2022-09-01
Category : Business & Economics
ISBN : 9783030486525

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Handbook of e-Tourism by Zheng Xiang,Matthias Fuchs,Ulrike Gretzel,Wolfram Höpken Pdf

This handbook provides an authoritative and truly comprehensive overview both of the diverse applications of information and communication technologies (ICTs) within the travel and tourism industry and of e-tourism as a field of scientific inquiry that has grown and matured beyond recognition. Leading experts from around the world describe cutting-edge ideas and developments, present key concepts and theories, and discuss the full range of research methods. The coverage accordingly encompasses everything from big data and analytics to psychology, user behavior, online marketing, supply chain and operations management, smart business networks, policy and regulatory issues – and much, much more. The goal is to provide an outstanding reference that summarizes and synthesizes current knowledge and establishes the theoretical and methodological foundations for further study of the role of ICTs in travel and tourism. The handbook will meet the needs of researchers and students in various disciplines as well as industry professionals. As with all volumes in Springer’s Major Reference Works program, readers will benefit from access to a continually updated online version.

Author : Wolfgang Nejdl,Judy Kay,Pearl Pu,Eelco Herder
Publisher : Springer
Page : 438 pages
File Size : 55,7 Mb
Release : 2008-07-30
Category : Computers
ISBN : 9783540709879

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Adaptive Hypermedia and Adaptive Web-Based Systems by Wolfgang Nejdl,Judy Kay,Pearl Pu,Eelco Herder Pdf

Adaptive Hypermedia has emerged as an important area of both academic and deployed research. It encompasses a broad range of research that will enable personalized, adaptive hypermedia systems to play an even more e?ective role in people’s lives. The Web has enabled the widespread use of many person- ized systems, such as recommenders, personalized ?lters and retrieval systems, e-learning systems and various forms of collaborative systems. Such systems have been widely deployed in diverse domains such as e-Commerce, e-Health, e-Government, digital libraries, personalized travel planning as well as tourist and cultural heritage services. They are particularly promising for users with special needs. The exciting possibilities of such deployed adaptive hypermedia systems rely on research progress in a broad range of areas such as: user pro- ing and modeling; acquisition, updating and management of user models; group modeling and community-based pro?ling;recommender systems and recomm- dation strategies; data mining for personalization; the Semantic Web; adaptive multimedia content authoring and delivery; ubiquitous computing environments and Smart Spaces; personalization for the plethora of mobile devices, such as PDAs, mobile phones and other hand-held devices; and pragmatics such as p- vacy, trust and security. Empirical studies of adaptive hypermedia and Web systems are also critical to informing future directions. The AdaptiveHypermediaconferenceshavebecomethe majorforumsforthe scienti?c exchange and presentation of research results on adaptive hypermedia and adaptive Web-based systems.

Author : Sean Owen,B. Ellen Friedman,Robin Anil,Ted Dunning
Publisher : Simon and Schuster
Page : 616 pages
File Size : 48,8 Mb
Release : 2011-10-04
Category : Computers
ISBN : 9781638355373

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Mahout in Action by Sean Owen,B. Ellen Friedman,Robin Anil,Ted Dunning Pdf

Summary Mahout in Action is a hands-on introduction to machine learning with Apache Mahout. Following real-world examples, the book presents practical use cases and then illustrates how Mahout can be applied to solve them. Includes a free audio- and video-enhanced ebook. About the Technology A computer system that learns and adapts as it collects data can be really powerful. Mahout, Apache's open source machine learning project, captures the core algorithms of recommendation systems, classification, and clustering in ready-to-use, scalable libraries. With Mahout, you can immediately apply to your own projects the machine learning techniques that drive Amazon, Netflix, and others. About this Book This book covers machine learning using Apache Mahout. Based on experience with real-world applications, it introduces practical use cases and illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability and how to apply these techniques against large data sets using the Apache Hadoop framework. This book is written for developers familiar with Java -- no prior experience with Mahout is assumed. Owners of a Manning pBook purchased anywhere in the world can download a free eBook from manning.com at any time. They can do so multiple times and in any or all formats available (PDF, ePub or Kindle). To do so, customers must register their printed copy on Manning's site by creating a user account and then following instructions printed on the pBook registration insert at the front of the book. What's Inside Use group data to make individual recommendations Find logical clusters within your data Filter and refine with on-the-fly classification Free audio and video extras Table of Contents Meet Apache Mahout PART 1 RECOMMENDATIONS Introducing recommenders Representing recommender data Making recommendations Taking recommenders to production Distributing recommendation computations PART 2 CLUSTERING Introduction to clustering Representing data Clustering algorithms in Mahout Evaluating and improving clustering quality Taking clustering to production Real-world applications of clustering PART 3 CLASSIFICATION Introduction to classification Training a classifier Evaluating and tuning a classifier Deploying a classifier Case study: Shop It To Me