@article {421,
	title = {The research of algorithm for data mining based on fuzzy theory},
	journal = {Journal of Digital Information Management},
	volume = {11},
	year = {2013},
	note = {Export Date: 10 July 2014},
	month = {2013},
	pages = {327 - 334},
	abstract = {Data Mining is a new filed in data processing research. Support Vector Machine (SVM) is one of the new methods using in data mining, which has gained great applicable success. However, there are still plenty of limitations in SVM. For example, SVM won{\textquoteright}t work if its training set contains uncertain information. In order to solve the problem presented above, this paper discusses the constraining programming of fuzzy chance and the characteristic of fuzzy classification as well as its expression methods. The algorithm for classifying Support Vector Machine is also included in this paper.},
	keywords = {Algorithm, Data mining, Fuzzy classification, Fuzzy linear separable, Fuzzy programming},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84890455119\&partnerID=40\&md5=cafd40536136512fd2e0485a0240a565},
	author = {Wang, A. and Li, J.}
}
@article {422,
	title = {The research on giant complex system using intelligent decision support system},
	journal = {Journal of Digital Information Management},
	volume = {11},
	year = {2013},
	note = {Export Date: 10 July 2014},
	month = {2013},
	pages = {335 - 341},
	abstract = {Mankind is confronted with an increasingly complex system, especially the major decision issues, such as organization and management, coordination, planning, forecasting, controlling and so on. Due to the complexity of the system, many fuzzy factors and the limitations of the existing complex giant system theory, there are still many problems to be solved. The research on the giant complex system based on the theory of fuzzy decision theory theoretically had been proving the reliability of the group decision and has established "the multijudgments information" fuzzy synthesis computational method. It has designed the corresponding multipurpose intelligent decision support system IDSS.},
	keywords = {Artificial intelligence, Decision support system, Fuzzy processing, Giant complex system},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84890477476\&partnerID=40\&md5=62072c647fcaedfc91f59a55e1124f4d},
	author = {Li, J. and Wang, A.}
}
@article {397,
	title = {Research on the anti-perspective correction algorithm of QR barcode},
	journal = {Journal of Digital Information Management},
	volume = {11},
	year = {2013},
	note = {Export Date: 10 July 2014},
	month = {2013},
	pages = {202 - 206},
	abstract = {2-D (2-dimension) bar code has many advantages compared with 1-D bar code, so it has many prevalent applications in recent days. However, there{\textquoteright}re several factors that affecting the sampling process, they lead to a certain degree of deformation towards the 2-D bar code. Furthermore, this deformation may too severe for 2-D bar code to be recognized. Generally, the main stream of twisted image correcting is based on the approach of control-point transformation. So how to locate the control point accurately becomes a key factor in 2-D bar code correcting. This paper develops a QR barcode searching graph and gets the precise location of control point. Experiment shows that our algorithm has good efficiency and accuracy.},
	keywords = {Image correction, Line fitting, Perspective transformation, QR code, Searching graphics},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84880830674\&partnerID=40\&md5=4b80f450374df6601877d816dd4cc9af},
	author = {Li, J. and Wang, Y.-W. and Wang, Y. and Chen, Y. and Wang, G.}
}
