Search Results for: Umap 16 User Modeling Adaptation And Personilization Conference

User Modeling, Adaptation, and Personalization

User Modeling, Adaptation, and Personalization

Author: Judith Masthoff

Publisher: Springer

ISBN: 9783642314544

Category: Computers

Page: 396

View: 155

This book constitutes the refereed proceedings of the 20 th International Conference on User Modeling, Adaptation, and Personalization, held in Montreal, Canada, in July 2012. The 22 long and 7 short papers of the Research Paper Track presented were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections on user engagement; trust; user motivation, attention, and effort; recommender systems (including topics such as matrix factorization, critiquing, noise and spam in recommender systems); user centered design and evaluation; educational data mining; modeling learners; user models in microblogging; and visualization. The Industry Paper Track covered innovative commercial implementations or applications of UMAP technologies, and experience in applying recent research advances in practice. 2 long and 1 short papers were accepted of 5 submissions.

User Modeling, Adaptation and Personalization

User Modeling, Adaptation and Personalization

Author: Joseph Konstan

Publisher: Springer

ISBN: 9783642223624

Category: Computers

Page: 464

View: 858

This book constitutes the proceedings of the third annual conference under the UMAP title, aptation, which resulted from the merger in 2009 of the successful biannual User Modeling (UM) and Adaptive Hypermedia (AH) conference series, held on Girona, Spain, in July 2011. The 27 long papers and 6 short papers presented together with15 doctoral consortium papers, 2 invited talks, and 3 industry panel papers were carefully reviewed and selected from 164 submissions. The tutorials and workshops were organized in topical sections on designing adaptive social applications, semantic adaptive social Web, and designing and evaluating new generation user modeling.

User Modeling, Adaptation and Personalization

User Modeling, Adaptation and Personalization

Author: Vania Dimitrova

Publisher: Springer

ISBN: 9783319087863

Category: Computers

Page: 510

View: 786

This book constitutes the thoroughly refereed proceedings of the 22nd International Conference on User Modeling, Adaption and Personalization, held in Aalborg, Denmark, in July 2014. The 23 long and 19 short papers of the research paper track were carefully reviewed and selected from 146 submissions. The papers cover the following topics: large scale personalization, adaptation and recommendation; Personalization for individuals, groups and populations; modeling individuals, groups and communities; Web dynamics and personalization; adaptive web-based systems; context awareness; social recommendations; user experience; user awareness and control; Affective aspects; UMAP underpinning by psychology models; privacy; perceived security and trust; behavior change and persuasion.

User Modeling, Adaptation, and Personalization

User Modeling, Adaptation, and Personalization

Author: Paul De Bra

Publisher: Springer Science & Business Media

ISBN: 9783642134692

Category: Computers

Page: 445

View: 940

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. In parallel to the printed book, each new volume is published electronically in LNCS Online. Detailed information on LNCS can be found at www.springer.com/Incs Proposals for publication should be sent to LNCS Editorial, Tiergartenstr. 17, 69121 Heidelberg, Germany E-mail: [email protected]

Digital Technologies and Instructional Design for Personalized Learning

Digital Technologies and Instructional Design for Personalized Learning

Author: Zheng, Robert

Publisher: IGI Global

ISBN: 9781522539414

Category: Education

Page: 391

View: 980

When facilitating high-quality education, using digital technology to personalize students' learning is a focus in the development of instruction. There is a need to unify the multifaceted directions in personalized learning by presenting a coherent and organized vision in the design of personalized learning using digital technology. Digital Technologies and Instructional Design for Personalized Learning is a critical scholarly resource that highlights the theories, principles, and learning strategies in personalized learning with digital technology. Featuring coverage on a broad range of topics, such as collaborative learning, instructional design, and computer-supported collaborative learning, this book is geared towards educators, professionals, school administrators, academicians, researchers, and students seeking current research on the area of personalized learning with digital technology.

User Modeling, Adaptation and Personalization

User Modeling, Adaptation and Personalization

Author: Francesco Ricci

Publisher: Springer

ISBN: 9783319202679

Category: Computers

Page: 404

View: 893

This book constitutes the refereed proceedings of the 23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015, held in Dublin, Ireland, in June/July 2015. The 25 long and 7 short papers of the research paper track were carefully reviewed and selected from 112 submissions. The papers reflect the conference theme "Contextualizing the World", highlighting the significance and impact of user modeling and adaptive technologies on a large number of everyday application areas such as: intelligent learning environments, recommender systems, e-commerce, advertising, personalized information retrieval and access, digital humanities, e-government, cultural heritage, and personalized health.

User Modeling, Adaption, and Personalization

User Modeling, Adaption, and Personalization

Author: Sandra Carberry

Publisher: Springer

ISBN: 9783642388446

Category: Computers

Page: 416

View: 180

This book constitutes the thoroughly refereed proceedings of the 21st International Conference on User Modeling, Adaption, and Personalization, held in Rome, Italy, in June 2013. The 21 long and 7 short papers of the research paper track were carefully reviewed and selected from numerous submissions. The papers cover the following topics: recommender systems, student modeling, social media and teams, human cognition, personality, privacy, web curation and user profiles, travel and mobile applications, and systems for elderly and disabled individuals.

User Modeling, Adaptation, and Personalization

User Modeling, Adaptation, and Personalization

Author: Geert-Jan Houben

Publisher: Springer

ISBN: 9783642022470

Category: Computers

Page: 488

View: 410

This book constitutes the proceedings of the First International Conference on User Modeling, Adaptation, and Personalization, held in Trento, Italy, on June 22-26, 2009. 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 53 papers presented together with 3 invited talks were carefully reviewed and selected from 125 submissions. The tutorials and workshops were organized in topical sections on constraint-based tutoring systems; new paradigms for adaptive interaction; adaption and personalization for Web 2.0; lifelong user modelling; personalization in mobile and pervasive computing; ubiquitous user modeling; user-centred design and evaluation of adaptive systems.

Collaborative Recommendations: Algorithms, Practical Challenges And Applications

Collaborative Recommendations: Algorithms, Practical Challenges And Applications

Author: Shlomo Berkovsky

Publisher: World Scientific

ISBN: 9789813275362

Category: Computers

Page: 736

View: 717

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.

Fashion Recommender Systems

Fashion Recommender Systems

Author: Nima Dokoohaki

Publisher: Springer Nature

ISBN: 9783030552183

Category: Science

Page: 145

View: 943

This book includes the proceedings of the first workshop on Recommender Systems in Fashion 2019. It presents a state of the art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail and fashion. The volume covers contributions from academic as well as industrial researchers active within this emerging new field. Recommender Systems are often used to solve different complex problems in this scenario, such as social fashion-based recommendations (outfits inspired by influencers), product recommendations, or size and fit recommendations. The impact of social networks and the influence that fashion influencers have on the choices people make for shopping is undeniable. For instance, many people use Instagram to learn about fashion trends from top influencers, which helps them to buy similar or even exact outfits from the tagged brands in the post. When traced, customers’ social behavior can be a very useful guide for online shopping websites, providing insights on the styles the customers are really interested in, and hence aiding the online shops in offering better recommendations and facilitating customers quest for outfits. Another well known difficulty with recommendation of similar items is the large quantities of clothing items which can be considered similar, but belong to different brands. Relying only on implicit customer behavioral data will not be sufficient in the coming future to distinguish between for recommendation that will lead to an item being purchased and kept, vs. a recommendation that might result in either the customer not following it, or eventually return the item. Finding the right size and fit for clothes is one of the major factors not only impacting customers purchase decision, but also their satisfaction from e-commerce fashion platforms. Moreover, fashion articles have important sizing variations. Finally, customer preferences towards perceived article size and fit for their body remain highly personal and subjective which influences the definition of the right size for each customer. The combination of the above factors leaves the customers alone to face a highly challenging problem of determining the right size and fit during their purchase journey, which in turn has resulted in having more than one third of apparel returns to be caused by not ordering the right article size. This challenge presents a huge opportunity for research in intelligent size and fit recommendation systems and machine learning solutions with direct impact on both customer satisfaction and business profitability.

Personalized Human-Computer Interaction

Personalized Human-Computer Interaction

Author: Mirjam Augstein

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 9783110552614

Category: Business & Economics

Page: 320

View: 348

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.