A hybrid filtering-based network document recommendation system in cloud storage. (27th November 2019)

• Record Type: Journal Article
• Authors: Wu, Yuezhong; Liu, Qin; Li, Changyun; Wang, Guojun
• Is Part Of: International journal of computational science and engineering. Volume 20:Number 2(2019)
• Page Start: 269
• Page End: 279
• Publication Date: 2019-11-27
• Subjects: user interest model -- collaborative filtering -- recommendation system -- cloud storage; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

Abstract

Since the key requirement of users is to efficiently obtain personalised services from mass network document resources, a hybrid filtering-based network document recommendation system is designed with the method of incorporating the content-based recommendation and collaborative filtering recommendation based on the powerful and extensible storage and computing power in cloud storage. The proposed system realises the main service module on Hadoop and Mahout platforms, and processes the documents containing the information of user interests by applying AHP-based attribute weighted fusion method. Based on the network interaction, the proposed system not only has advantages on the extensible storage space and high recommendation precision but also has an essential role in realising network resources sharing and personalised recommendation.