Download Umap 18 full books in PDF, epub, and Kindle. Read online Umap 18 ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
This book constitutes the proceedings of the Second International Conference on User Modeling, Adaptation, and Personalization, held on Big Island, HI, USA, in June 2010. This annual conference was merged from the biennial conference series User Modeling, UM, and the conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH. The 26 long papers and 6 short papers presented together with 7 doctoral consortium papers, 2 invited talks, and 4 industry panel papers were carefully reviewed and selected from 161 submissions. The tutorials and workshops were organized in topical sections on intelligent techniques for web personalization and recommender systems; pervasive user modeling and personalization; user models for motivational systems; adaptive collaboration support; architectures and building blocks of web-based user adaptive systems; adaptation and personalization in e-b/learning using pedagogic conversational agents; and user modeling and adaptation for daily routines.
Book Synopsis User Modeling, Adaptation, and Personalization by : Paul De Bra
Download or read book User Modeling, Adaptation, and Personalization written by Paul De Bra and published by Springer. This book was released on 2010-06-16 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Second International Conference on User Modeling, Adaptation, and Personalization, held on Big Island, HI, USA, in June 2010. This annual conference was merged from the biennial conference series User Modeling, UM, and the conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH. The 26 long papers and 6 short papers presented together with 7 doctoral consortium papers, 2 invited talks, and 4 industry panel papers were carefully reviewed and selected from 161 submissions. The tutorials and workshops were organized in topical sections on intelligent techniques for web personalization and recommender systems; pervasive user modeling and personalization; user models for motivational systems; adaptive collaboration support; architectures and building blocks of web-based user adaptive systems; adaptation and personalization in e-b/learning using pedagogic conversational agents; and user modeling and adaptation for daily routines.
This book on self-improving systems is the seventh in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tutoring, self-improving systems, data visualization) in intelligent tutoring system (ITS) design. This book focuses on self-improving systems. The discussion chapters in this book examine topics through the lens of the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, distribute ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes.
Book Synopsis Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Self-Improving Systems by : Benjamin Goldberg
Download or read book Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Self-Improving Systems written by Benjamin Goldberg and published by U.S. Army Combat Capabilities Development Command – Soldier Center. This book was released on 2019-10-23 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on self-improving systems is the seventh in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tutoring, self-improving systems, data visualization) in intelligent tutoring system (ITS) design. This book focuses on self-improving systems. The discussion chapters in this book examine topics through the lens of the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, distribute ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes.
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.
Book Synopsis Recommender Systems Handbook by : Francesco Ricci
Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer Nature. This book was released on 2022-04-21 with total page 1053 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
This two-volume set LNCS 14465-14466 constitutes the proceedings of the 31st International Symposium on Graph Drawing and Network Visualization, GD 2023, held in Isola delle Femmine, Palermo, Italy, in September 2023. The 31 full papers, 7 short papers, presented together with 2 invited talks, and one contest report, were thoroughly reviewed and selected from the 100 submissions. The abstracts of 11 posters presented at the conference can be found in the back matter of the volume. The contributions were organized in topical sections as follows: beyond planarity; crossing numbers; linear layouts; geometric aspects; visualization challenges; graph representations; graph decompositions; topological aspects; parameterized complexity for drawings; planar graphs; frameworks; algorithmics.
Book Synopsis Graph Drawing and Network Visualization by : Michael A. Bekos
Download or read book Graph Drawing and Network Visualization written by Michael A. Bekos and published by Springer Nature. This book was released on 2024-01-11 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 14465-14466 constitutes the proceedings of the 31st International Symposium on Graph Drawing and Network Visualization, GD 2023, held in Isola delle Femmine, Palermo, Italy, in September 2023. The 31 full papers, 7 short papers, presented together with 2 invited talks, and one contest report, were thoroughly reviewed and selected from the 100 submissions. The abstracts of 11 posters presented at the conference can be found in the back matter of the volume. The contributions were organized in topical sections as follows: beyond planarity; crossing numbers; linear layouts; geometric aspects; visualization challenges; graph representations; graph decompositions; topological aspects; parameterized complexity for drawings; planar graphs; frameworks; algorithmics.
Personalized and adaptive systems employ user models to adapt content, services, interaction or navigation to individual users’ needs. User models can be inferred from implicitly observed information, such as the user’s interaction history or current location, or from explicitly entered information, such as user profile data or ratings. Applications of personalization include item recommendation, location-based services, learning assistance and the tailored selection of interaction modalities. With the transition from desktop computers to mobile devices and ubiquitous environments, the need for adapting to changing contexts is even more important. However, this also poses new challenges concerning privacy issues, user control, transparency, and explainability. In addition, user experience and other human factors are becoming increasingly important. This book describes foundations of user modeling, discusses user interaction as a basis for adaptivity, and showcases several personalization approaches in a variety of domains, including music recommendation, tourism, and accessible user interfaces.
Book Synopsis Personalized Human-Computer Interaction by : Mirjam Augstein
Download or read book Personalized Human-Computer Interaction written by Mirjam Augstein and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-09-23 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized and adaptive systems employ user models to adapt content, services, interaction or navigation to individual users’ needs. User models can be inferred from implicitly observed information, such as the user’s interaction history or current location, or from explicitly entered information, such as user profile data or ratings. Applications of personalization include item recommendation, location-based services, learning assistance and the tailored selection of interaction modalities. With the transition from desktop computers to mobile devices and ubiquitous environments, the need for adapting to changing contexts is even more important. However, this also poses new challenges concerning privacy issues, user control, transparency, and explainability. In addition, user experience and other human factors are becoming increasingly important. This book describes foundations of user modeling, discusses user interaction as a basis for adaptivity, and showcases several personalization approaches in a variety of domains, including music recommendation, tourism, and accessible user interfaces.
This handbook is the first book ever covering the area of Multimodal Learning Analytics (MMLA). The field of MMLA is an emerging domain of Learning Analytics and plays an important role in expanding the Learning Analytics goal of understanding and improving learning in all the different environments where it occurs. The challenge for research and practice in this field is how to develop theories about the analysis of human behaviors during diverse learning processes and to create useful tools that could augment the capabilities of learners and instructors in a way that is ethical and sustainable. Behind this area, the CrossMMLA research community exchanges ideas on how we can analyze evidence from multimodal and multisystem data and how we can extract meaning from this increasingly fluid and complex data coming from different kinds of transformative learning situations and how to best feed back the results of these analyses to achieve positive transformative actions on those learning processes. This handbook also describes how MMLA uses the advances in machine learning and affordable sensor technologies to act as a virtual observer/analyst of learning activities. The book describes how this “virtual nature” allows MMLA to provide new insights into learning processes that happen across multiple contexts between stakeholders, devices and resources. Using such technologies in combination with machine learning, Learning Analytics researchers can now perform text, speech, handwriting, sketches, gesture, affective, or eye-gaze analysis, improve the accuracy of their predictions and learned models and provide automated feedback to enable learner self-reflection. However, with this increased complexity in data, new challenges also arise. Conducting the data gathering, pre-processing, analysis, annotation and sense-making, in a way that is meaningful for learning scientists and other stakeholders (e.g., students or teachers), still pose challenges in this emergent field. This handbook aims to serve as a unique resource for state of the art methods and processes. Chapter 11 of this book is available open access under a CC BY 4.0 license at link.springer.com.
Book Synopsis The Multimodal Learning Analytics Handbook by : Michail Giannakos
Download or read book The Multimodal Learning Analytics Handbook written by Michail Giannakos and published by Springer Nature. This book was released on 2022-10-08 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is the first book ever covering the area of Multimodal Learning Analytics (MMLA). The field of MMLA is an emerging domain of Learning Analytics and plays an important role in expanding the Learning Analytics goal of understanding and improving learning in all the different environments where it occurs. The challenge for research and practice in this field is how to develop theories about the analysis of human behaviors during diverse learning processes and to create useful tools that could augment the capabilities of learners and instructors in a way that is ethical and sustainable. Behind this area, the CrossMMLA research community exchanges ideas on how we can analyze evidence from multimodal and multisystem data and how we can extract meaning from this increasingly fluid and complex data coming from different kinds of transformative learning situations and how to best feed back the results of these analyses to achieve positive transformative actions on those learning processes. This handbook also describes how MMLA uses the advances in machine learning and affordable sensor technologies to act as a virtual observer/analyst of learning activities. The book describes how this “virtual nature” allows MMLA to provide new insights into learning processes that happen across multiple contexts between stakeholders, devices and resources. Using such technologies in combination with machine learning, Learning Analytics researchers can now perform text, speech, handwriting, sketches, gesture, affective, or eye-gaze analysis, improve the accuracy of their predictions and learned models and provide automated feedback to enable learner self-reflection. However, with this increased complexity in data, new challenges also arise. Conducting the data gathering, pre-processing, analysis, annotation and sense-making, in a way that is meaningful for learning scientists and other stakeholders (e.g., students or teachers), still pose challenges in this emergent field. This handbook aims to serve as a unique resource for state of the art methods and processes. Chapter 11 of this book is available open access under a CC BY 4.0 license at link.springer.com.
Book Synopsis University of Michigan Executive System for the IBM 7090 Computer, September, 1965 by : University of Michigan Computing Center
Download or read book University of Michigan Executive System for the IBM 7090 Computer, September, 1965 written by University of Michigan Computing Center and published by . This book was released on 1965 with total page 1072 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This book aims at guiding the educators from a variety of available technologies to support learning and teaching by discussing the learning benefits and the challenges that interactive technology imposes. This guidance is based on practical experiences gathered through developing and integrating them into varied educational settings. It compiles experiences gained with various interactive technologies, offering a comprehensive perspective on the use and potential value of interactive technologies to support learning and teaching. Taken together, the chapters provide a broader view that does not focus exclusively on the uses of technology in educational settings, but also on the impact and ability of technology to improve the learning and teaching processes. The book addresses the needs of researchers, educators and other stakeholders in the area of education interested in learning how interactive technologies can be used to overcome key educational challenges.
Book Synopsis Learning in a Digital World by : Paloma Díaz
Download or read book Learning in a Digital World written by Paloma Díaz and published by Springer. This book was released on 2019-06-29 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at guiding the educators from a variety of available technologies to support learning and teaching by discussing the learning benefits and the challenges that interactive technology imposes. This guidance is based on practical experiences gathered through developing and integrating them into varied educational settings. It compiles experiences gained with various interactive technologies, offering a comprehensive perspective on the use and potential value of interactive technologies to support learning and teaching. Taken together, the chapters provide a broader view that does not focus exclusively on the uses of technology in educational settings, but also on the impact and ability of technology to improve the learning and teaching processes. The book addresses the needs of researchers, educators and other stakeholders in the area of education interested in learning how interactive technologies can be used to overcome key educational challenges.
Online learning has increasingly been viewed as a possible way to remove barriers associated with traditional face-to-face teaching, such as overcrowded classrooms and shortage of certified teachers. While online learning has been recognized as a possible approach to deliver more desirable learning outcomes, close to half of online students drop out as a result of student-related, course-related, and out-of-school-related factors (e.g., poor self-regulation; ineffective teacher-student, student-student, and platform-student interactions; low household income). Many educators have expressed concern over students who unexpectedly begin to struggle and appear to fall off track without apparent reason. A well-implemented early warning system, therefore, can help educators identify students at risk of dropping out and assign and monitor interventions to keep them on track for graduation. Despite the popularity of early warning systems, research on their design and implementation is sparse. Early Warning Systems and Targeted Interventions for Student Success in Online Courses is a cutting-edge research publication that examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of early warning systems and targeted interventions and discusses their implications for policy and practice. Moreover, this book will review common challenges of early warning systems and dashboard design and will explore design principles and data visualization tools to make data more understandable and, therefore, more actionable. Highlighting a range of topics such as curriculum design, game-based learning, and learning support, it is ideal for academicians, policymakers, administrators, researchers, education professionals, instructional designers, data analysts, and students.
Book Synopsis Early Warning Systems and Targeted Interventions for Student Success in Online Courses by : Glick, Danny
Download or read book Early Warning Systems and Targeted Interventions for Student Success in Online Courses written by Glick, Danny and published by IGI Global. This book was released on 2020-06-26 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online learning has increasingly been viewed as a possible way to remove barriers associated with traditional face-to-face teaching, such as overcrowded classrooms and shortage of certified teachers. While online learning has been recognized as a possible approach to deliver more desirable learning outcomes, close to half of online students drop out as a result of student-related, course-related, and out-of-school-related factors (e.g., poor self-regulation; ineffective teacher-student, student-student, and platform-student interactions; low household income). Many educators have expressed concern over students who unexpectedly begin to struggle and appear to fall off track without apparent reason. A well-implemented early warning system, therefore, can help educators identify students at risk of dropping out and assign and monitor interventions to keep them on track for graduation. Despite the popularity of early warning systems, research on their design and implementation is sparse. Early Warning Systems and Targeted Interventions for Student Success in Online Courses is a cutting-edge research publication that examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of early warning systems and targeted interventions and discusses their implications for policy and practice. Moreover, this book will review common challenges of early warning systems and dashboard design and will explore design principles and data visualization tools to make data more understandable and, therefore, more actionable. Highlighting a range of topics such as curriculum design, game-based learning, and learning support, it is ideal for academicians, policymakers, administrators, researchers, education professionals, instructional designers, data analysts, and students.
It is our great pleasure to welcome you to the 26th ACM International Conference on User modeling, Adaptation and personalization - UMAP 2018. UMAP is the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users. UMAP is the successor of the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It has traditionally been organized under the auspices of User Modeling Inc. Since 2016, UMAP is an ACM conference, sponsored by ACM SIGCHI and SIGWEB. UMAP 2018 is a very special conference, as this is the very first time UMAP will be located in Asia! We hope to meet many like-minded researchers from Singapore and other Asian countries. The conference spans a wide scope of topics related to user modeling, adaptation, and personalization. UMAP 2018 is focused on bringing together cutting-edge research from user interaction and modeling, adaptive technologies, and delivery platforms. It includes high-quality peer-reviewed papers featuring substantive new research in one of five research tracks, each chaired by leaders in the field: Adaptive Hypermedia and the Semantic Web (track chairs Peter Brusilovsky and Geert-Jan Houben) Intelligent User interfaces (track chairs Shlomo Berkovsky and Markus Schedl) Personalized Recommender Systems (track chairs Dietmar Jannach and Markus Zanker) Personalized Social Web (track chairs Cecile Paris and Julita Vassileva) Technology-Enhanced Adaptive Learning (track chairs Olga Santos and Carla Limongelli) The call for papers attracted 137 submissions from 33 different countries on all continents except Antarctica: Argentina, Australia, Austria, Belgium, Brazil, Canada, China, Cyprus, Denmark, Finland, France, Germany, India, Indonesia, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Nigeria, Norway, Pakistan, Philippines, Portugal, Saudi Arabia, Singapore, South Korea, Spain, Sweden, Switzerland, United Kingdom, and the United States The international program committee consisted of 131 reviewers. Each submission received at least 3 reviews. After the initial reviews were submitted, the designated track chairs (TCs) facilitated discussion amongst reviewers in order to resolve differences and correct misunderstandings. The TCs then provided a recommendation to the Program Chairs. The final decisions were based on these recommendations, meta-reviews, and reviewer scores. Moreover, 10 papers were accepted as extended abstracts, and 13 were included in Late Breaking Results track (LBR). We thank Hui Fang and Pasquale Lops, LBR and Demo Chairs, for their efforts on selecting addition papers submitted to this track. As a result, there are 3 Demos, 3 Theory, Opinion and Reflection papers, and 20 Late Breaking Results papers presented in the iv UMAP poster sessions, which collectively showcase the wide spectrum of novel ideas and latest results in user modeling, adaptation and personalization. We also encourage attendees to attend the keynote presentations; these valuable and insightful talks guide us to a better understanding of the future. Running Recommendations: Personalisation Opportunities for Health and Fitness, Barry Smith (University College Dublin, Ireland) Robots that Listen to People's Hearts: the Role of Emotions in the Communication between Humans and Social Robots, Ana Paiva (University of Lisbon, Portugal) Interpreting User Input Intention in Natural Human Computer Interaction, Yuanchun Shi (Tsinghua University, China)
Book Synopsis UMAP '18 by : Umap
Download or read book UMAP '18 written by Umap and published by . This book was released on 2018-11-08 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is our great pleasure to welcome you to the 26th ACM International Conference on User modeling, Adaptation and personalization - UMAP 2018. UMAP is the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users. UMAP is the successor of the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It has traditionally been organized under the auspices of User Modeling Inc. Since 2016, UMAP is an ACM conference, sponsored by ACM SIGCHI and SIGWEB. UMAP 2018 is a very special conference, as this is the very first time UMAP will be located in Asia! We hope to meet many like-minded researchers from Singapore and other Asian countries. The conference spans a wide scope of topics related to user modeling, adaptation, and personalization. UMAP 2018 is focused on bringing together cutting-edge research from user interaction and modeling, adaptive technologies, and delivery platforms. It includes high-quality peer-reviewed papers featuring substantive new research in one of five research tracks, each chaired by leaders in the field: Adaptive Hypermedia and the Semantic Web (track chairs Peter Brusilovsky and Geert-Jan Houben) Intelligent User interfaces (track chairs Shlomo Berkovsky and Markus Schedl) Personalized Recommender Systems (track chairs Dietmar Jannach and Markus Zanker) Personalized Social Web (track chairs Cecile Paris and Julita Vassileva) Technology-Enhanced Adaptive Learning (track chairs Olga Santos and Carla Limongelli) The call for papers attracted 137 submissions from 33 different countries on all continents except Antarctica: Argentina, Australia, Austria, Belgium, Brazil, Canada, China, Cyprus, Denmark, Finland, France, Germany, India, Indonesia, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Nigeria, Norway, Pakistan, Philippines, Portugal, Saudi Arabia, Singapore, South Korea, Spain, Sweden, Switzerland, United Kingdom, and the United States The international program committee consisted of 131 reviewers. Each submission received at least 3 reviews. After the initial reviews were submitted, the designated track chairs (TCs) facilitated discussion amongst reviewers in order to resolve differences and correct misunderstandings. The TCs then provided a recommendation to the Program Chairs. The final decisions were based on these recommendations, meta-reviews, and reviewer scores. Moreover, 10 papers were accepted as extended abstracts, and 13 were included in Late Breaking Results track (LBR). We thank Hui Fang and Pasquale Lops, LBR and Demo Chairs, for their efforts on selecting addition papers submitted to this track. As a result, there are 3 Demos, 3 Theory, Opinion and Reflection papers, and 20 Late Breaking Results papers presented in the iv UMAP poster sessions, which collectively showcase the wide spectrum of novel ideas and latest results in user modeling, adaptation and personalization. We also encourage attendees to attend the keynote presentations; these valuable and insightful talks guide us to a better understanding of the future. Running Recommendations: Personalisation Opportunities for Health and Fitness, Barry Smith (University College Dublin, Ireland) Robots that Listen to People's Hearts: the Role of Emotions in the Communication between Humans and Social Robots, Ana Paiva (University of Lisbon, Portugal) Interpreting User Input Intention in Natural Human Computer Interaction, Yuanchun Shi (Tsinghua University, China)
