Header menu link for other important links
Deep Learning Model Schemes to Address the Scrutability and In-Memory Purchase Issues in Recommender System
J sharon moses,
Published in Springer Singapore
Volume: 750
Pages: 326 - 335
Recommender systems are used widely in each and every web services to recommend and suggest user interested information or products. The advancement of digital information era and pain in traversing the vast amount of information made users to realise the importance of intelligent recommender systems. Intelligent recommender system suffers over many issues some among them are scrutability, scalability and in-memory purchase problem. In-memory purchase problem is one of the currently persisting recommender system problems. In this paper the deep learning models based recommendation scheme are framed to address the scrutability and in-memory purchase issue of the recommender system. Initially the working of deep learning models like feed forward and recurrent neural network are discussed. Then the recommendation schemes based on the deep learning models in addressing the issues of the recommender system are detailed. © Springer Nature Singapore Pte Ltd. 2017.
About the journal
JournalData powered by TypesetCommunications in Computer and Information Science Information, Communication and Computing Technology
PublisherData powered by TypesetSpringer Singapore
Open AccessNo