Context Aware Collaborative Prediction
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Context-Aware Collaborative Prediction
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.
Proceedings of the 1st Workshop on Deep Learning for Recommender Systems
Workshop on Deep Learning for Recommender Systems Sep 15, 2016-Sep 15, 2016 Boston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Location- and Context-Awareness
Context-awareness is one of the drivers of the ubiquitous computing paradigm. Well-designed context modeling and context retrieval approaches are key p- requisites in any context-aware system. Location is one of the primary aspects of all major context models — together with time, identity and activity. From the technical side, sensing, fusing and distributing location and other context information is as important as providing context-awareness to applications and services in pervasive systems. Thematerialsummarizedinthisvolumewasselectedforthe1stInternational Workshop on Location- and Context-Awareness (LoCA 2005) held in coope- tion with the 3rd International Conference on Pervasive Computing 2005. The workshop was organized by the Institute of Communications and Navigation of the German Aerospace Center (DLR) in Oberpfa?enhofen, and the Mobile and Distributed Systems Group of the University of Munich. During the workshop, novel positioning algorithms and location sensing te- niques were discussed, comprising not only enhancements of singular systems, like positioning in GSM or WLAN, but also hybrid technologies, such as the integration of global satellite systems with inertial positioning. Furthermore, - provements in sensor technology, as well as the integration and fusion of sensors, were addressed both on a theoretical and on an implementation level. Personal and con?dential data, such as location data of users, have p- found implications for personal information privacy. Thus privacy protection, privacy-oriented location-aware systems, and how privacy a?ects the feasibility and usefulness of systems were also addressed in the workshop.