원문정보
초록
영어
Recommendation Systems are information technologies that E-commerce merchants have adopted so that online shoppers can receive suggestions on items that might be interesting or complementing to their purchased items. These systems stipulate valuable assistance to the user’s purchasing decisions, and provide quality of push service. Traditionally, Recommendation Systems have been designed using a centralized system, but information service is growing vast with a rapid and strong scalability. The next generation of information technology such as Cloud Computing and Big Data Environment has handled massive data and is able to support enormous processing power. Nevertheless, analytic technologies are lacking the different capabilities when processing big data. Accordingly, we are trying to design a conceptual service model with a proposed new algorithm and user adaptation on dynamic recommendation service for big data environment.
목차
1. Introduction
2. Related Works
2.1 Hadoop
2.2 Hadoop Distributed File System
2.3 Hive and HiveQL
3. Recommender Service-Oriented Algorithm
3.1 Re-SOA
3.2 User-Oriented Algorithm (UOA)
3.3 SOA and UOA for Recommender Service
4. Querying Service for Recommender Service
5. Conclusions
References