Results 11 to 20 of about 2,095 (214)
Application of Improved K-Means Algorithm in Collaborative Recommendation System
Journal of Applied Mathematics, 2022 With the explosive growth of information resources in the age of big data, mankind has gradually fallen into a serious “information overload” situation. In the face of massive data, collaborative filtering algorithm plays an important role in information
Hui Jing
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Structured collaborative filtering [PDF]
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011 In a general collaborative filtering (CF) setting, a user profile contains a set of previously rated items and is used to represent the user's interest. Unfortunately, most CF approaches ignore the underlying structure of user profiles. In this paper, we argue that a certain class of interest is best represented jointly by several items, drawing an ...
Alejandro Bellogín +2 more
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Collaborative Filtering Algorithm Combining Ontology Semantics and User Attribute [PDF]
Jisuanji gongcheng, 2019 When dealing with massive data,the traditional collaborative filtering recommendation algorithm has the data sparsity and the long tail effect of the items,resulting in low recommendation accuracy.Aiming at this problem,combining ontology semantics and ...
WANG Guang, JIANG Li, DONG Shuaihan, LI Feng
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On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets
Information, 2022 The typical goal of a collaborative filtering algorithm is the minimisation of the deviation between rating predictions and factual user ratings so that the recommender system offers suggestions for appropriate items, achieving a higher prediction value.
Dionisis Margaris +2 more
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Perceptron Collaborative Filtering
International Journal for Research in Applied Science and Engineering Technology, 2023 Abstract: While multivariate logistic regression classifiers are a great way of implementing collaborative filtering - a method of making automatic predictions about the interests of a user by collecting preferences or taste information from many other users, we can also achieve similar results using neural networks.
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The intellectual system of movies recommendations based on the collaborative filtering
Journal of Education, Health and Sport, 2022 The investigation deals with designing and developing of intellectual system of movies recommendations based on the collaborative filtering using the Python software environment.
Stepan Sitkar +7 more
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Context-Similarity Collaborative Filtering Recommendation
IEEE Access, 2020 This article proposes a new method to overcome the sparse data problem of the collaborative filtering models (CF models) by considering the homologous relationship between users or items calculated on contextual attributes when we build the CF models. In
Hiep Xuan Huynh +6 more
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An Improved Dynamic Collaborative Filtering Algorithm Based on LDA
IEEE Access, 2021 Currently, available collaborative filtering (CF) algorithms often utilize user behavior data to generate recommendations. The similarity calculation between users is mostly based on the scores, without considering the explicit attributes of the users ...
Meng Di-Fei +3 more
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Classification and Comparison of the Hybrid Collaborative Filtering Systems [PDF]
International Journal of Research in Industrial Engineering, 2017 Recommender systems have become fundamental applications in overloaded information domains like e-commerce. These systems aim to provide users with suggestions about items that are likely to be of their interest.
F. S. Gohari, M.J. Tarokh
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Active Collaborative Filtering
CoRR, 2012 Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of online and interactive CF: given the current ratings associated with a user, what queries (new ratings) would most improve the quality of the recommendations made?
Craig Boutilier +2 more
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