Earticle

초록

영어

As the wide use of radio frequency identification (RFID) technology, such wireless sensor network has created enormous data in supply chain management, manufacturing sites, retailor sections, as well as health care domain. In order to discovery the invaluable information and knowledge from such massive RFID data, this paper introduces a data mining approach based on graphic theory to pick out the useful information and knowledge from logistics RFID data. This approach considers the complex relationship of different RFID data and uses graphic model to build up the logistics path. That means the logistics information stored in RFID data is converted by graphic diagram, which could be mined by the proposed approach over OLAP. The inquiry efficiency has been greatly improved through experimental results.

목차

Abstract
 1. Introduction
 2. RFID Data Warehouse
  2.1. RFID Logistics Dataset.
  2.2. Architecture of the RFID data warehouse.
 3. RFID Frequent Path
  3.1. Flow cube
 4. Data Mining Approach based on Graphic Theory
 5. Experiments and Discussion
 6. Conclusions
 References

키워드

저자

• Lianjun Yi [ School of Science and Technology; Gannan Normal University, Ganzhou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605