Big Data Recommender Systems

Osman Khalid is assistant professor at the department of computer sciences, COMSATS Institute of Information Technology, Abbottabad, Pakistan. His research interests include recommender systems, trust and reputation system, disaster response systems, delay tolerant networks, wireless networks, and fog computing.Samee U. Khan is associate professor of electrical and computer engineering at the North Dakota State University, USA. His research interests include optimization, robustness, and security of systems.Albert Y. Zomaya is chair professor of high performance computing & networking and Australian research council professorial fellow in the School of Information Technologies, The University of Sydney, Australia. He is also the director of the Centre for Distributed and High Performance Computing.

• Chapter 1: Introduction to big data recommender systems - volume 1Chapter 2: Theoretical foundations for recommender systemsChapter 3: Benchmarking big data recommendation algorithms using Hadoop orApache SparkChapter 4: Efficient and socio-aware recommendation approaches for bigdata networked systemsChapter 5: Novel hybrid approaches for big data recommendationsChapter 6: Deep generative models for recommender systemsChapter 7: Recommendation algorithms for unstructured big data such as text, audio, image and videoChapter 8: Deep segregation of plastic (DSP): segregation of plastic and nonplastic using deep learningChapter 9: Spatiotemporal recommendation with big geo-social networking dataChapter 10: Recommender system for predicting malicious Android applicationsChapter 11: Security threats and their mitigation in big data recommender systemsChapter 12: User's privacy in recommendation systems applying online social network data: a survey and taxonomyChapter 13: Private entity resolution for big data on Apache Spark using multiple phonetic codesChapter 14: Deep learning architecture for big data analytics in detecting intrusions and malicious URL