Earticle

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

Abstract
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

키워드

저자

• Kim Ryong [ Doctoral Candidate, MIS Major, Dept. of Management, ChungNam National University ] First Author
• Kyung-Hye Park [ Professor, School of Business, College of Economics and Management, ChungNam National University ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005