Recommender Systems for Learning

Author: Nikos Manouselis
Publisher: Springer Science & Business Media
ISBN: 146144361X
Format: PDF, Kindle
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Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Recommender Systems for Learning

Author: Nikos Manouselis
Publisher: Springer Science & Business Media
ISBN: 146144361X
Format: PDF, ePub, Mobi
Download and Read
Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Group Recommender Systems

Author: Alexander Felfernig
Publisher: Springer
ISBN: 3319750674
Format: PDF, ePub
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This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The authors summarize different technologies and applications of group recommender systems. They include an in-depth discussion of state-of-the-art algorithms, an overview of industrial applications, an inclusion of the aspects of decision biases in groups, and corresponding de-biasing approaches. The book includes a discussion of basic group recommendation methods, aspects of human decision making in groups, and related applications. A discussion of open research issues is included to inspire new related research. The book serves as a reference for researchers and practitioners working on group recommendation related topics.

Recommender Systems for Technology Enhanced Learning

Author: Nikos Manouselis
Publisher: Springer Science & Business Media
ISBN: 1493905309
Format: PDF, Docs
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As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years. Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices. Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

Encyclopedia of Information Science and Technology Fourth Edition

Author: Khosrow-Pour, D.B.A., Mehdi
Publisher: IGI Global
ISBN: 1522522565
Format: PDF, ePub, Docs
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In recent years, our world has experienced a profound shift and progression in available computing and knowledge sharing innovations. These emerging advancements have developed at a rapid pace, disseminating into and affecting numerous aspects of contemporary society. This has created a pivotal need for an innovative compendium encompassing the latest trends, concepts, and issues surrounding this relevant discipline area. During the past 15 years, the Encyclopedia of Information Science and Technology has become recognized as one of the landmark sources of the latest knowledge and discoveries in this discipline. The Encyclopedia of Information Science and Technology, Fourth Edition is a 10-volume set which includes 705 original and previously unpublished research articles covering a full range of perspectives, applications, and techniques contributed by thousands of experts and researchers from around the globe. This authoritative encyclopedia is an all-encompassing, well-established reference source that is ideally designed to disseminate the most forward-thinking and diverse research findings. With critical perspectives on the impact of information science management and new technologies in modern settings, including but not limited to computer science, education, healthcare, government, engineering, business, and natural and physical sciences, it is a pivotal and relevant source of knowledge that will benefit every professional within the field of information science and technology and is an invaluable addition to every academic and corporate library.

Ubiquitous Learning Environments and Technologies

Author: Kinshuk
Publisher: Springer
ISBN: 3662446596
Format: PDF, Kindle
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This book focuses on the design and architecture of ubiquitous learning environments, associated technologies, various learning scenarios supported by these environments, and different contexts that arise in environments where the seamless immersion of formal and informal activities and interactions has the potential to contribute to the learning process. With particular focus on adaptivity for individual learners, the book explores the diminishing boundaries of formal and informal learning, and the potential of location-aware context-sensitive approaches that are emerging as successors to the Web 2.0 paradigm.

Encyclopedia of E Commerce Development Implementation and Management

Author: Lee, In
Publisher: IGI Global
ISBN: 1466697881
Format: PDF, ePub, Mobi
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The convenience of online shopping has driven consumers to turn to the internet to purchase everything from clothing to housewares and even groceries. The ubiquity of online retail stores and availability of hard-to-find products in the digital marketplace has been a catalyst for a heighted interest in research on the best methods, techniques, and strategies for remaining competitive in the era of e-commerce. The Encyclopedia of E-Commerce Development, Implementation, and Management is an authoritative reference source highlighting crucial topics relating to effective business models, managerial strategies, promotional initiatives, development methodologies, and end-user considerations in the online commerce sphere. Emphasizing emerging research on up-and-coming topics such as social commerce, the Internet of Things, online gaming, digital products, and mobile services, this multi-volume encyclopedia is an essential addition to the reference collection of both academic and corporate libraries and caters to the research needs of graduate-level students, researchers, IT developers, and business professionals. .

Persuasive Recommender Systems

Author: Kyung-Hyan Yoo
Publisher: Springer Science & Business Media
ISBN: 146144702X
Format: PDF
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Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

Recommender Systems for Social Tagging Systems

Author: Leandro Balby Marinho
Publisher: Springer Science & Business Media
ISBN: 1461418941
Format: PDF, Kindle
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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.

Trust for Intelligent Recommendation

Author: Touhid Bhuiyan
Publisher: Springer Science & Business Media
ISBN: 1461468957
Format: PDF, ePub, Mobi
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Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world “friend of a friend” recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required. This book proposes a trust interference technique called Directed Series Parallel Graph (DSPG) that has empirically outperformed other popular trust inference algorithms, such as TidalTrust and MoleTrust. For times when reliable explicit trust data is not available, this book outlines a new method called SimTrust for developing trust networks based on a user’s interest similarity. To identify the interest similarity, a user’s personalized tagging information is used. However, particular emphasis is given in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbors used in the automated recommender system. Through a series of case studies and empirical results, this book highlights the effectiveness of this tag-similarity based method over the traditional collaborative filtering approach, which typically uses rating data. Trust for Intelligent Recommendation is intended for practitioners as a reference guide for developing improved, trust-based recommender systems. Researchers in a related field will also find this book valuable.