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RecSysRecommender Systems (International Conference)
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Instead of recommender systems that reveal what you most want to hear, they'd inject a set of countervailing views.
Machine learning solutions can be applied for image-based diagnosis, object recognition in images, detection of hardware defects and design of recommender systems, amongst other things.
Recommender systems are utilized for personalizing information sources for users by guiding them in a personalized way to interesting items selected from myriad of available options (Lops et al.
The special tacks program included sessions and papers on AI and CyberSecurity, AI in Games, Serious Games, and Multimedia, AI in Health-Care Informatics, Applications of Artificial Intelligence in Business and Industry, Applied Natural Language Processing, Artificial Intelligence for Big Social Data Analysis, Autonomous Robots and Agents, Case-Based Reasoning, Data Mining, Learning from Heterogeneous Data Analytics, Intelligent Learning Technologies, Intelligent Support for Decision Making, Natural Language Processing of Ancient and Other Low-Resource Languages, Nonclassical Logic, Recommender Systems, Semantic / Logics / Information Extraction and AI, and Uncertain Reasoning.
Recommender systems can maximize investment returns in stock portfolio investments.
Knowledge Based Recommender Systems use the knowledge about users' necessities to infer recommendations not requiring a great amount of data like another approaches [4].
Evaluating recommender systems for supportive technologies," User Modeling and Adaptation for Daily Routines, pp.
Currently, personalized services such as recommender systems have become common in our daily lives.
The recommender systems are most popular intelligent software systems of the information filtering systems that applied in a various domains for example movies, music, books, jokes, restaurant, financial services [8], and Twitter followers [9].
Recommender systems are decision support systems used in e-commerce to help navigate customers to the right product (Bauer & Nanopoulos, 2014; Cheung, Kwok, Law, & Tsui, 2003; Chung, Hsu, & Huang, 2013; Ekstrand, 2010; Gan & Jiang, 2013)
presented two different approaches for building hybrid collaborative content recommender systems to overcome the new item issue [5].