Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015, Article ID 802505, 7 pages
Research Article

Research on FCM and NHL Based High Order Mining Driven by Big Data

1Resource Sharing and Promotion Center, Institute of Science and Technology Information of China, Beijing 100038, China
2School of Computer, North China Institute of Scientific and Technology, Beijing 101601, China

Received 31 July 2014; Revised 14 November 2014; Accepted 21 November 2014

Academic Editor: Xiaosheng Si

Copyright © 2015 Zhen Peng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to get the high order evaluation and correlation degree among big data with the characteristics of multidimension and multigranularity, an FCM and NHL based high order mining algorithm driven by big data is proposed, which is a kind of machine learning based on qualitative knowledge. The algorithm is applied in scientific and technical talent forecast. Driven by the big data of scientific research track of scientific and technical talents, the index system is designed and the big data is automatically acquired and processed. Accordingly, the high order evaluations in dimension level and target level can be inferred by the correlation weights mining. And the outstanding young talents in material field in 2014 have been actively recommended to review department for decision-making.