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https://www.researchgate.net/publication/225139953_Recommender_Systems_Using_Support_Vector_Machines
Recommender Systems Using Support Vector Machines Conference Paper (PDF Available) in Lecture Notes in Computer Science 3579:387-393 · December 2005 with 2,356 Reads How we …
https://link.springer.com/chapter/10.1007/11531371_50
This study focuses on improving the performance of recommender systems by using data mining techniques. This paper proposes an SVM based recommender system. Furthermore this paper presents the methods for improving the performance of the SVM based recommender system in two aspects: feature subset selection and parameter optimization.Cited by: 13
https://stats.stackexchange.com/questions/68125/support-vector-machines-and-recommender-algorithms
Support Vector Machines and Recommender Algorithms. Ask Question Asked 6 years, 1 month ago. ... I tried to think of ways of using SVMs for the rating prediction problem. However, I could not make much progress. Also, I could not explain why SVMs are not good for this problem. ... How do recommender systems incorporate user characteristics? 3.
https://cseweb.ucsd.edu/classes/fa17/cse291-b/reading/Rendle2010FM.pdf
of Support Vector Machines (SVM) with factorization models. Like SVMs, FMs are a general predictor working with any real valued feature vector. In contrast to SVMs, FMs model all interactions between variables using factorized parameters. Thus they are able to estimate interactions even in problems with huge
https://dl.acm.org/citation.cfm?id=944795
Recommender systems use historical data on user preferences and other available data on users (for example, demographics) and items (for example, taxonomy) to predict items a new user might like. Applications of these methods include recommending items for purchase and personalizing the browsing experience on a web-site.Cited by: 163
https://medium.com/datadriveninvestor/recommender-systems-using-rbm-79d65fcadf8f
Apr 18, 2019 · Content-Based Filtering Recommender Systems; ... where ui is the user profile vector based on the latent factors and vi ... Restricted Boltzmann machines can be used to build a recommender system ...Author: Manish Nayak
https://www.coursera.org/lecture/machine-learning/using-an-svm-sKQoJ
Depending on what support vector machine software package you use, it may ask you to implement a kernel function, or to implement the similarity function. So if you're using an octave or MATLAB implementation of an SVM, it may ask you to provide a function to compute a particular feature of the kernel.
https://www.coursera.org/lecture/machine-learning/content-based-recommendations-uG59z
We don't regularize over the bias terms. The sum is from k equals 1 through n. So if you minimize this as a function of theta j you get a good solution, you get a pretty good estimate of a parameter vector theta j with which to make predictions for user j's movie ratings. For recommender systems, I'm gonna change this notation a little bit.
https://www.researchgate.net/publication/220704992_Understanding_Support_Vector_Machine_Classifications_via_a_Recommender_System-Like_Approach
Download Citation Understanding Support Vector Machine Classifications via a Recommender System-Like Approach Support vector machines are a …
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