Abstract
In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of experts. However, the previous expert-based recommender systems are limited in that the same experts are suggested for all users. In this paper, we study personalized expert identification problem, assuming each user needs different kinds and levels of expert help. We demonstrate the feasibility of personalized expert-based recommendation; we present and analyze an SVM framework for finding personalized experts.
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Chung, Y., Jung, HW., Kim, J., Lee, JH. (2013). Personalized Expert-Based Recommender System: Training C-SVM for Personalized Expert Identification. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2013. Lecture Notes in Computer Science(), vol 7988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39712-7_33
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DOI: https://doi.org/10.1007/978-3-642-39712-7_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39711-0
Online ISBN: 978-3-642-39712-7
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