Context Aware Ranking With Factorization Models

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Context-Aware Ranking with Factorization Models

Author : Steffen Rendle
Publisher : Springer Science & Business Media
ISBN 13 : 3642168973
Total Pages : 183 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Context-Aware Ranking with Factorization Models by : Steffen Rendle

Download or read book Context-Aware Ranking with Factorization Models written by Steffen Rendle and published by Springer Science & Business Media. This book was released on 2010-11-11 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Context-aware ranking is an important task with many applications. E.g. in recommender systems items (products, movies, ...) and for search engines webpages should be ranked. In all these applications, the ranking is not global (i.e. always the same) but depends on the context. Simple examples for context are the user for recommender systems and the query for search engines. More complicated context includes time, last actions, etc. The major problem is that typically the variable domains (e.g. customers, products) are categorical and huge, the observations are very sparse and only positive events are observed. In this book, a generic method for context-aware ranking as well as its application are presented. For modelling a new factorization based on pairwise interactions is proposed and compared to other tensor factorization approaches. For learning, the `Bayesian Context-aware Ranking' framework consisting of an optimization criterion and algorithm is developed. The second main part of the book applies this general theory to the three scenarios of item, tag and sequential-set recommendation. Furthermore extensions of time-variant factors and one-class problems are studied. This book generalizes and builds on work that has received the `WWW 2010 Best Paper Award', the `WSDM 2010 Best Student Paper Award' and the `ECML/PKDD 2009 Best Discovery Challenge Award'.

Context-Aware Ranking with Factorization Models

Author : Steffen Rendle
Publisher : Springer
ISBN 13 : 3642168981
Total Pages : 183 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

Book Synopsis Context-Aware Ranking with Factorization Models by : Steffen Rendle

Download or read book Context-Aware Ranking with Factorization Models written by Steffen Rendle and published by Springer. This book was released on 2010-11-18 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Context-aware ranking is an important task with many applications. E.g. in recommender systems items (products, movies, ...) and for search engines webpages should be ranked. In all these applications, the ranking is not global (i.e. always the same) but depends on the context. Simple examples for context are the user for recommender systems and the query for search engines. More complicated context includes time, last actions, etc. The major problem is that typically the variable domains (e.g. customers, products) are categorical and huge, the observations are very sparse and only positive events are observed. In this book, a generic method for context-aware ranking as well as its application are presented. For modelling a new factorization based on pairwise interactions is proposed and compared to other tensor factorization approaches. For learning, the `Bayesian Context-aware Ranking' framework consisting of an optimization criterion and algorithm is developed. The second main part of the book applies this general theory to the three scenarios of item, tag and sequential-set recommendation. Furthermore extensions of time-variant factors and one-class problems are studied. This book generalizes and builds on work that has received the `WWW 2010 Best Paper Award', the `WSDM 2010 Best Student Paper Award' and the `ECML/PKDD 2009 Best Discovery Challenge Award'.

Metalearning

Author : Pavel Brazdil
Publisher : Springer Science & Business Media
ISBN 13 : 3540732624
Total Pages : 182 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Metalearning by : Pavel Brazdil

Download or read book Metalearning written by Pavel Brazdil and published by Springer Science & Business Media. This book was released on 2008-11-26 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Recommender Systems

Author : Charu C. Aggarwal
Publisher : Springer
ISBN 13 : 3319296590
Total Pages : 518 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Recommender Systems by : Charu C. Aggarwal

Download or read book Recommender Systems written by Charu C. Aggarwal and published by Springer. This book was released on 2016-03-28 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.

Context-Aware Collaborative Prediction

Author : Shu Wu
Publisher : Springer
ISBN 13 : 9811053731
Total Pages : 74 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Context-Aware Collaborative Prediction by : Shu Wu

Download or read book Context-Aware Collaborative Prediction written by Shu Wu and published by Springer. This book was released on 2018-03-10 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents two collaborative prediction approaches based on contextual representation and hierarchical representation, and their applications including context-aware recommendation, latent collaborative retrieval and click-through rate prediction. The proposed techniques offer significant improvements over current methods, the key determinants being the incorporated contextual representation and hierarchical representation. To provide a background to the core ideas presented, it offers an overview of contextual modeling and the theory of contextual representation and hierarchical representation, which are constructed for the joint interaction of entities and contextual information. The book offers a rich blend of theory and practice, making it a valuable resource for students, researchers and practitioners who need to construct systems of information retrieval, data mining and recommendation systems with contextual information.

Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges

Author : I. Tiddi
Publisher : IOS Press
ISBN 13 : 1643680811
Total Pages : 314 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges by : I. Tiddi

Download or read book Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges written by I. Tiddi and published by IOS Press. This book was released on 2020-05-06 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.

Information Retrieval Technology

Author : Fu Lee Wang
Publisher : Springer Nature
ISBN 13 : 3030428354
Total Pages : 207 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Information Retrieval Technology by : Fu Lee Wang

Download or read book Information Retrieval Technology written by Fu Lee Wang and published by Springer Nature. This book was released on 2020-02-26 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th Information Retrieval Technology Conference, AIRS 2019, held in Hong Kong, China, in November 2019.The 14 full papers presented together with 3 short papers were carefully reviewed and selected from 27 submissions. The scope of the conference covers applications, systems, technologies and theory aspects of information retrieval in text, audio, image, video and multimedia data.

Recommender Systems for Social Tagging Systems

Author : Leandro Balby Marinho
Publisher : Springer Science & Business Media
ISBN 13 : 1461418941
Total Pages : 116 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Recommender Systems for Social Tagging Systems by : Leandro Balby Marinho

Download or read book Recommender Systems for Social Tagging Systems written by Leandro Balby Marinho and published by Springer Science & Business Media. This book was released on 2012-02-10 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.

The Semantic Web – ISWC 2019

Author : Chiara Ghidini
Publisher : Springer Nature
ISBN 13 : 303030793X
Total Pages : 794 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis The Semantic Web – ISWC 2019 by : Chiara Ghidini

Download or read book The Semantic Web – ISWC 2019 written by Chiara Ghidini and published by Springer Nature. This book was released on 2019-10-17 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community. The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.

Matrix and Tensor Factorization Techniques for Recommender Systems

Author : Panagiotis Symeonidis
Publisher : Springer
ISBN 13 : 3319413570
Total Pages : 101 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Matrix and Tensor Factorization Techniques for Recommender Systems by : Panagiotis Symeonidis

Download or read book Matrix and Tensor Factorization Techniques for Recommender Systems written by Panagiotis Symeonidis and published by Springer. This book was released on 2017-01-29 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.

Educational Recommender Systems and Technologies: Practices and Challenges

Author : Santos, Olga C.
Publisher : IGI Global
ISBN 13 : 161350490X
Total Pages : 362 pages
Book Rating : 4.6/5 (135 download)

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Book Synopsis Educational Recommender Systems and Technologies: Practices and Challenges by : Santos, Olga C.

Download or read book Educational Recommender Systems and Technologies: Practices and Challenges written by Santos, Olga C. and published by IGI Global. This book was released on 2011-12-31 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems have shown to be successful in many domains where information overload exists. This success has motivated research on how to deploy recommender systems in educational scenarios to facilitate access to a wide spectrum of information. Tackling open issues in their deployment is gaining importance as lifelong learning becomes a necessity of the current knowledge-based society. Although Educational Recommender Systems (ERS) share the same key objectives as recommenders for e-commerce applications, there are some particularities that should be considered before directly applying existing solutions from those applications. Educational Recommender Systems and Technologies: Practices and Challenges aims to provide a comprehensive review of state-of-the-art practices for ERS, as well as the challenges to achieve their actual deployment. Discussing such topics as the state-of-the-art of ERS, methodologies to develop ERS, and architectures to support the recommendation process, this book covers researchers interested in recommendation strategies for educational scenarios and in evaluating the impact of recommendations in learning, as well as academics and practitioners in the area of technology enhanced learning.

Information Retrieval

Author : Pavel Braslavski
Publisher : Springer
ISBN 13 : 3319417185
Total Pages : 202 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Information Retrieval by : Pavel Braslavski

Download or read book Information Retrieval written by Pavel Braslavski and published by Springer. This book was released on 2016-07-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 9th Russian Summer School on Information Retrieval, RuSSIR 2015, held in Saint Petersburg, Russia, in August 2015. The volume includes 5 tutorial papers, summarizing lectures given at the event, and 6 revised papers from the school participants. The papers focus on various aspects of information retrieval.

Machine Learning and Data Analytics for Solving Business Problems

Author : Bader Alyoubi
Publisher : Springer Nature
ISBN 13 : 3031184831
Total Pages : 214 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Machine Learning and Data Analytics for Solving Business Problems by : Bader Alyoubi

Download or read book Machine Learning and Data Analytics for Solving Business Problems written by Bader Alyoubi and published by Springer Nature. This book was released on 2022-12-15 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

Graph-Based Social Media Analysis

Author : Ioannis Pitas
Publisher : CRC Press
ISBN 13 : 1498719058
Total Pages : 436 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Graph-Based Social Media Analysis by : Ioannis Pitas

Download or read book Graph-Based Social Media Analysis written by Ioannis Pitas and published by CRC Press. This book was released on 2016-04-19 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear alge

Modeling Intention in Email

Author : Vitor R. Carvalho
Publisher : Springer Science & Business Media
ISBN 13 : 3642199550
Total Pages : 111 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Modeling Intention in Email by : Vitor R. Carvalho

Download or read book Modeling Intention in Email written by Vitor R. Carvalho and published by Springer Science & Business Media. This book was released on 2011-11-06 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everyday more than half of American adult internet users read or write email messages at least once. The prevalence of email has significantly impacted the working world, functioning as a great asset on many levels, yet at times, a costly liability. In an effort to improve various aspects of work-related communication, this work applies sophisticated machine learning techniques to a large body of email data. Several effective models are proposed that can aid with the prioritization of incoming messages, help with coordination of shared tasks, improve tracking of deadlines, and prevent disastrous information leaks. Carvalho presents many data-driven techniques that can positively impact work-related email communication and offers robust models that may be successfully applied to future machine learning tasks.

Model-Driven Development of Advanced User Interfaces

Author : Heinrich Hussmann
Publisher : Springer Science & Business Media
ISBN 13 : 3642145612
Total Pages : 320 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Model-Driven Development of Advanced User Interfaces by : Heinrich Hussmann

Download or read book Model-Driven Development of Advanced User Interfaces written by Heinrich Hussmann and published by Springer Science & Business Media. This book was released on 2011-01-16 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-Driven Development (MDD) has become an important paradigm in software development. It uses models as primary artifacts in the development process. This book provides an outstanding overview as well as deep insights into the area of model-driven development of user interfaces, which is an emerging topic in the intersection of Human-Computer-Interaction and Software-Engineering. The idea of this book is based on the very successful workshop series of “Model-Driven Development of Advanced User Interfaces (MDDAUI)”. It has been written by the leading researchers and practitioners in the field of model-driven development of user interfaces and offer a variety of solutions and examples for • Architectures and environments for the generation of user interfaces • User interface development for specific domains and purposes • Model-driven development in the context of ambient intelligence • Concepts supporting model-driven development of user interfaces

Collaborative Recommendations: Algorithms, Practical Challenges And Applications

Author : Shlomo Berkovsky
Publisher : World Scientific
ISBN 13 : 9813275367
Total Pages : 736 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Collaborative Recommendations: Algorithms, Practical Challenges And Applications by : Shlomo Berkovsky

Download or read book Collaborative Recommendations: Algorithms, Practical Challenges And Applications written by Shlomo Berkovsky and published by World Scientific. This book was released on 2018-11-30 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e-commerce, multimedia and Web content. Collaborative-based methods have been the focus of recommender systems research for more than two decades.The unique feature of the compendium is the technical details of collaborative recommenders. The book chapters include algorithm implementations, elaborate on practical issues faced when deploying these algorithms in large-scale systems, describe various optimizations and decisions made, and list parameters of the algorithms.This must-have title is a useful reference materials for researchers, IT professionals and those keen to incorporate recommendation technologies into their systems and services.