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【期刊论文】FTT Algorithm of Web Pageviews for Personalized Recommendation
覃征, Shen Yunfei, Qin Zheng, Yuan Kun, and Luo Xiaowei
LNCS 4185, pp. 133-139, 2006.,-0001,():
-1年11月30日
As the need for personalized services sharply increases caused by the booming of Internet, Web-based data-mining is becoming a valuable sources of thoughts and theory to satisfy the personalized system function. The characters of personalized data-mining is reviewed and discussed in the beginning, and then an innovative algorithm (FP-Tree time-validity algorithm) of Web pageviews, based on personalization, is raised. More authentic information can be efficiently got by adding time-validity coefficient to FTT-Tree storage structure to implement increment mining.
Data mining,, Web mining,, Personalization,, Association rule,, Time, v, a, l, idity.,
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【期刊论文】Adaptive Mobile Cooperation Model Based on Context Awareness
覃征, Weihong Wang , and Zheng Qin
LNCS 3841, pp. 1189-1192, 2006.,-0001,():
-1年11月30日
Aiming at the mobile cooperation in the mobile computing environment, a novel model, CA-AMCM (Adaptive Mobile Cooperation Model based on Context-Awareness), was proposed. Firstly, we give the sets of correlation context, the principle and definition about the relation each other among contexts. Then, we describe the abstraction of context information, which is necessary to group cooperation in mobile computing. We express context with ontology theory and deduct with first-order predication. After that, CA-AMCM model was constructed based on it. At last, we apply the model to the MECP (Mobile Embedded Cooperation Platform). The practice indicates that the model provides a powerful means for advancing group cooperation intelligence.
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【期刊论文】MATE: A Visual Based 3D Shape Descriptor*
覃征, LENG Biao, QIN Zheng, , CAO Xiaoman, WEI Tao and ZHANG Zhuxi
Chinese Journal of Electronics Vol.18, No.2, Apr. 2009,-0001,():
-1年11月30日
Since 3D models have been widely applied in many research areas, the techniques for content-based 3D model retrieval become necessary. In this paper, a novel visual based 3D shape descriptor called MATE is proposed. A modi-ed Principal component analysis (PCA) method for model normalization is presented at-rst. Sec-ondly, a new Adjacent angle distance Fourier (AADF) al-gorithm is proposed. Then the original two-viewed Dbucrer method is presented to extract characteristics of projected images. Finally, based on the modi-ed PCA method, the shape descriptor MATE is proposed by combining AADF, Tchebichef and two-viewed Dbu®er. Experimental results show that the descriptor MATE provides better retrieval performance than the best current descriptors.
3D model retrie, v, a, l, ,, Shape des, c, r, i, p, t, or,, Visual similarity.,
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【期刊论文】Automatic Combination of Feature Descriptors for Effective 3D Shape Retrieval
覃征, Biao Leng and Zheng Qin
LNCS 4418, pp. 36-46, 2007.,-0001,():
-1年11月30日
We focus on improving the effectiveness of content-based 3D shape retrieval. Motivated by retrieval performance of several ndividual 3D model feature vectors, we propose a novel method, called prior knowledge based automatic weighted combination, to improve the retrieval effectiveness. The method dynamically determines the weighting scheme for different feature vectors based on the prior knowledge. The experimental results show that the proposed method provides significant improvements on retrieval effectiveness of 3D shape search with several measures on a standard 3D database. Compared with two existing combination methods, the prior knowledge weighted combination technique has gained better retrieval effectiveness.
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覃征, Xing-Chen Heng and Zheng Qin
LNCS 3645, pp. 209-217, 2005.,-0001,():
-1年11月30日
This paper proposes a general formalism for evaluating hybrid Bayesian networks. The formalism approximates a hybrid Bayesian network into the form, called fuzzy partial least-squares Bayesian network (FPBN). The form replaces each continuous variable whose descendants include discrete variables by a partner discrete variable and adding a directed link from that partner discrete variable to the continuous one. The partner discrete variable is acquired by the discretization of the original continuous variable with a fuzzification algorithm based on the structure adaptive-tuning neural network model. In addition, the dependence between the partner discrete variable and the original continuous variable is approximated by fuzzy sets, and the dependence between a continuous variable and its continuous and discrete parents is approximated by a conditional Gaussian regression (CGR) distribution in which partial least-squares (PLS) is proposed as an alternative method for computing the vector of regression parameter. The experimental results are included to demonstrate the performances of the new approach.
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