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Reviews in Recommender Systems: 2022
Frontiers in Big Data is delighted to present the ‘Reviews in Recommender Systems’ series of article collections. Reviews in Recommender Systems will publish high-quality scholarly review papers on key topics in recommender systems and their applications in our everyday lives, in search engines, online retail, news, entertainment, travel, social networks, and much more. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. We anticipate the research presented will promote discussion in the Big Data community that will translate to best practice applications in further research, industry, real-world implementations, public health, and policy settings.
Personalized Human-Computer Interaction
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.
Mining, Modeling, and Recommending 'Things' in Social Media
This book constitutes the thoroughly refereed joint post-workshop proceedings of the 4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013, held in Prague, Czech Republic, in September 2013, and the 4th International Workshop on Modeling Social Media, MSM 2013, held in Paris, France, in May 2013. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. The focus is on collective intelligence in ubiquitous and social environments. Issues tackled include personalization in social streams, recommendations exploiting social and ubiquitous data, and efficient information processing in social systems. Furthermore, this book presents work dealing with the problem of mining patterns from ubiquitous social data, including mobility mining and exploratory methods for ubiquitous data analysis.
Advances in Speech and Music Technology
This book presents advances in speech and music in the domain of audio signal processing. The book begins with introductory chapters on the basics of speech and music, and then proceeds to computational aspects of speech and music, including music information retrieval and spoken language processing. The authors discuss the intersection in the field of computer science, musicology and speech analysis, and how the multifaceted nature of speech and music information processing requires unique algorithms, systems using sophisticated signal processing, and machine learning techniques that better extract useful information. The authors discuss how a deep understanding of both speech and music in ...
Advances in Bias and Fairness in Information Retrieval
This book constitutes the refereed proceedings of the 4th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2023, held in Dublin, Ireland, in April 2023. The 10 full papers and 4 short papers included in this book were carefully reviewed and selected from 36 submissions. The present recent research in the following topics: biases exploration and assessment; mitigation strategies against biases; biases in newly emerging domains of application, including healthcare, Wikipedia, and news, novel perspectives; and conceptualizations of biases in the context of generative models and graph neural networks.
User Modeling, Adaptation and Personalization
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.
Technology-Enhanced Learning for a Free, Safe, and Sustainable World
This book constitutes the proceedings of the 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, held in Bolzano, Italy, in September 2021. The 21 research full papers and 28 short papers presented in this volume were carefully reviewed and selected from 98 submissions. The European Conference on Technology-Enhance Learning, is committed to address global challenges and quality education. The papers deal with the Sustainable Development Goals, particularly SDG 4 and SDG 10, to help to reduce the existing gaps and inequalities between countries and regions from around the world in terms of inclusiveness, equity, access, and quality of education.
Advances in Information Retrieval
The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, and 12 reproducibility papers, 10 doctoral consortium papers were carefully reviewed and selected from 489 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
