Table of contents
About this book
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.
- Book Title Context-Aware Collaborative Prediction
- Series Title SpringerBriefs in Computer Science
- Series Abbreviated Title SpringerBriefs Computer Sci.
- DOI https://doi.org/10.1007/978-981-10-5373-3
- Copyright Information The Author(s) 2017
- Publisher Name Springer, Singapore
- eBook Packages Computer Science Computer Science (R0)
- Softcover ISBN 978-981-10-5372-6
- eBook ISBN 978-981-10-5373-3
- Series ISSN 2191-5768
- Series E-ISSN 2191-5776
- Edition Number 1
- Number of Pages XI, 69
- Number of Illustrations 1 b/w illustrations, 8 illustrations in colour
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
Data Mining and Knowledge Discovery
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