An Improved KNN Algorithm for Product Quality and Safety Incident Information Tracking

DOI

10.2991/nceece-15.2016.264How to use a DOI?

Keywords

Web news; product quality and safety incident; KNN

Abstract

In recent years, product quality and safety event shave happened frequently, which poses a threat to the health and property safety of consumers. With the development of the Internet, Web news has become one of the important channels for information release regarding product quality and safety issues. Therefore, identifying and tracking these incidents information plays an important role in providing early warning for product quality and safety problems. This paper presents K-Nearest Neighbor(KNN) algorithm as the methods of event and the topic tracking, and takes into account the correlation of product quality and safety WEB news to improve KNN algorithm. The "hole shoes" event as an example is to verify the feasibility of the proposed algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Yingcheng Xu
AU  - Zhongbao Sun
AU  - Wei Jiang
PY  - 2015/12
DA  - 2015/12
TI  - An Improved KNN Algorithm for Product Quality and Safety Incident Information Tracking
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 1476
EP  - 1479
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.264
DO  - 10.2991/nceece-15.2016.264
ID  - Xu2015/12
ER  -