Abstract
Motivated by recent works of natural language processing, this chapter introduces the concept of contextual operation for context-aware modeling. This operation represents each context value with a latent vector and models the contextual information as a semantic operation on the user and item. Besides, the contextual operating tensor is used to capture the common semantic effects of contexts. This chapter introduces notations and fundamental concepts of context representation, and then thoroughly presents the contextual operating tensor (COT) model. Finally, the process of parameter inference and the optimization algorithm is discussed.
Parts of this chapter is reprinted from [1], with permission from IEEE.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wu, S., Liu, Q., Wang, L., Tan, T.: Contextual operation for recommender systems. IEEE TKDE 28, 2000–2012 (2016)
Koren, Y., Bell, R.: Advances in collaborative filtering. In: Recommender Systems Handbook, pp. 145–186. Springer, Berlin (2011)
Koren, Y., Bell, R., Volinsky, C.: Matrix factorization techniques for recommender systems. Computer 42(8), 30–37 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 The Author(s)
About this chapter
Cite this chapter
Wu, S., Liu, Q., Wang, L., Tan, T. (2017). Contextual Operation. In: Context-Aware Collaborative Prediction. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-5373-3_3
Download citation
DOI: https://doi.org/10.1007/978-981-10-5373-3_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5372-6
Online ISBN: 978-981-10-5373-3
eBook Packages: Computer ScienceComputer Science (R0)