A Recommender System for Library Based on Hadoop Ecosystem
Abstract
With the rapid development of network and information technology, big data already exists in various fields. Its main features include large amount of data (Volume), speed (Velocity) and diversity (Variety). The information system of library also has the characteristics of big data which have a large number of collected books, readers, and diverse resources. Because of the era of big data, libraries need to assist the reader to rapidly get the appropriate information from a large number of collected resources in the library information system. It is an important issue to establish the suitable recommender system in order to recommend readers to the related library resources and to enhance the usage of library resources. In this paper, a recommender system for library based on Hadoop Ecosystem is proposed. First, it uses Hadoop ecosystem to import data from the information system of library. Furthermore, the association rule and parallel CLARANS are implemented in Hadoop platform for the library recommender system. The proposed approach can assist readers to find the suitable resources in library.
DOI
10.12783/dtmse/icmsme2016/7507
10.12783/dtmse/icmsme2016/7507
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