This paper focuses on some key problems in web community discovery and link analysis.Based on the topic-oriented technology,the characteristics of a bipartite graph are studied.An Х bipartite core set is introduced t...This paper focuses on some key problems in web community discovery and link analysis.Based on the topic-oriented technology,the characteristics of a bipartite graph are studied.An Х bipartite core set is introduced to more clearly define extracting ways.By scanning the topic subgraph to construct Х bipartite graph and then prune the graph with i and j ,an Х bipartite core set,which is also the minimum element of a community,can be found.Finally,a hierarchical clustering algorithm is applied to many Х bipartite core sets and the dendrogram of the community inner construction is obtained.The correctness of the constructing and pruning method is proved and the algorithm is designed.The typical datasets in the experiment are prepared according to the way in HITS（hyperlink-induced topic search）.Ten topics and four search engines are chosen and the returned results are integrated.The modularity,which is a measure of the strength of the community structure in the social network,is used to validate the efficiency of the proposed method.The experimental results show that the proposed algorithm is effective and efficient.展开更多
The features of DNA sequence fragments were extracted from the distribution density of the condons in the individual cases of DNA sequence fragments. Based on the polarity of side chain radicals of amino acids molecul...The features of DNA sequence fragments were extracted from the distribution density of the condons in the individual cases of DNA sequence fragments. Based on the polarity of side chain radicals of amino acids molecules, the amino acids were classified into five categories, and the frequencies of these five categories were calculated. This kind of feature extraction based on the biological meanings not only took the content of basic groups into consideration, but also considered the marshal ing sequence of the basic groups. The hierarchical clustering analysis and BP neural network were used to classify the DNA sequence fragments. The results showed that the classification results of these two kinds of algo-rithms not only had high accuracy, but also had high consistence, indicating that this kind of feature extraction was superior over the traditional feature extraction which only took the features of basic groups into consideration.展开更多
In this paper, classification models are used as tools to make final decision. Fuzzy method provides the mathematical tools for quantitative analysis and dealing with ambiguous concepts. Analytic Hierarchy Process (AH...In this paper, classification models are used as tools to make final decision. Fuzzy method provides the mathematical tools for quantitative analysis and dealing with ambiguous concepts. Analytic Hierarchy Process (AHP) is used to obtain the weight of each index and enables examiners to visualize the decision process and obtain more reasonable evaluation values to solve some problems. An example is given at the end of this paper.展开更多
Crowded scene analysis is currently a hot and challenging topic in computer vision field. The ability to analyze motion patterns from videos is a difficult, but critical part of this problem. In this paper, we propose...Crowded scene analysis is currently a hot and challenging topic in computer vision field. The ability to analyze motion patterns from videos is a difficult, but critical part of this problem. In this paper, we propose a novel approach for the analysis of motion patterns by clustering the tracklets using an unsupervised hierarchical clustering algorithm, where the similarity between tracklets is measured by the Longest Common Subsequences. The tracklets are obtained by tracking dense points under three effective rules, therefore enabling it to capture the motion patterns in crowded scenes. The analysis of motion patterns is implemented in a completely unsupervised way, and the tracklets are clustered automatically through hierarchical clustering algorithm based on a graphic model. To validate the performance of our approach, we conducted experimental evaluations on two datasets. The results reveal the precise distributions of motion patterns in current crowded videos and demonstrate the effectiveness of our approach.展开更多
We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area b...We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area between the minimum and maximum range of an input feature value into three equal parts. Then, we produced self-organizing product maps using classification data inputs. Finally, we applied our method to five product types and confirmed its effectiveness. In this paper, we propose a method for selecting alternatives from a product map, in which we have located a favorite several examples of selecting alternatives and making decisions using cluster, and/or from a favorite component map. We then show the AHP （Analytic Hierarchy Process）.展开更多
OBJECTIVE: To analyze the component law of Chinese medicines in fuming-washing therapy for knee osteoarthritis(KOA), and develop new fuming-washing prescriptions for KOA through unsupervised data mining methods.METHOD...OBJECTIVE: To analyze the component law of Chinese medicines in fuming-washing therapy for knee osteoarthritis(KOA), and develop new fuming-washing prescriptions for KOA through unsupervised data mining methods.METHODS: Chinese medicine recipes for fuming-washing therapy for KOA were collected and recorded in a database. The correlation coefficient among herbs, core combinations of herbs, andnew prescriptions were analyzed using modified mutual information, complex system entropy cluster, and unsupervised hierarchical clustering, respectively.RESULTS: Based on analysis of 345 Chinese medicine recipes for fuming-washing therapy, 68 herbs occurred frequently, 33 herb pairs occurred frequently, and 12 core combinations were found.Five new fuming-washing recipes for KOA were developed.CONCLUSION: Chinese medicines for fuming-washing therapy of KOA mainly consist of wind-dampness-dispelling and cold-dispersing herbs, blood-activating and stasis-resolving herbs,and wind-dampness-dispelling and heat-clearing herbs. The treatment of fuming-washing therapy for KOA also includes dispelling wind-dampness and dispersing cold, activating blood and resolving stasis, and dispelling wind-dampness and clearing heat. Zhenzhutougucao(Herba Speranskiae Tuberculatae), Honghua(Flos Carthami), Niuxi(Radix Achyranthis Bidentatae), Shenjincao(Herba Lycopodii Japonici), Weilingxian(Radix et Rhizoma Clematidis Chinensis), Chuanwu(Radix Aconiti), Haitongpi(Cortex Erythrinae Variegatae), Ruxiang(Olibanum),Danggui(Radix Angelicae Sinensis), Caowu(Radix Aconiti Kusnezoffii), Moyao(Myrrha), and Aiye(Folium Artemisiae Argyi) are the main herbs used in the fuming-washing treatment for KOA.展开更多
基金The National Natural Science Foundation of China(No.60773216)the National High Technology Research and Development Program of China(863Program)(No.2006AA010109)+1 种基金the Natural Science Foundation of Renmin University of China(No.06XNB052)Free Exploration Project(985 Project of Renmin University of China)(No.21361231)
文摘This paper focuses on some key problems in web community discovery and link analysis.Based on the topic-oriented technology,the characteristics of a bipartite graph are studied.An Х bipartite core set is introduced to more clearly define extracting ways.By scanning the topic subgraph to construct Х bipartite graph and then prune the graph with i and j ,an Х bipartite core set,which is also the minimum element of a community,can be found.Finally,a hierarchical clustering algorithm is applied to many Х bipartite core sets and the dendrogram of the community inner construction is obtained.The correctness of the constructing and pruning method is proved and the algorithm is designed.The typical datasets in the experiment are prepared according to the way in HITS（hyperlink-induced topic search）.Ten topics and four search engines are chosen and the returned results are integrated.The modularity,which is a measure of the strength of the community structure in the social network,is used to validate the efficiency of the proposed method.The experimental results show that the proposed algorithm is effective and efficient.
基金Supported by the Natural Science Foundation of Zhejiang Province(LY13A010007)~~
文摘The features of DNA sequence fragments were extracted from the distribution density of the condons in the individual cases of DNA sequence fragments. Based on the polarity of side chain radicals of amino acids molecules, the amino acids were classified into five categories, and the frequencies of these five categories were calculated. This kind of feature extraction based on the biological meanings not only took the content of basic groups into consideration, but also considered the marshal ing sequence of the basic groups. The hierarchical clustering analysis and BP neural network were used to classify the DNA sequence fragments. The results showed that the classification results of these two kinds of algo-rithms not only had high accuracy, but also had high consistence, indicating that this kind of feature extraction was superior over the traditional feature extraction which only took the features of basic groups into consideration.
文摘In this paper, classification models are used as tools to make final decision. Fuzzy method provides the mathematical tools for quantitative analysis and dealing with ambiguous concepts. Analytic Hierarchy Process (AHP) is used to obtain the weight of each index and enables examiners to visualize the decision process and obtain more reasonable evaluation values to solve some problems. An example is given at the end of this paper.
基金supported in part by National Basic Research Program of China (973 Program) under Grant No. 2011CB302203the National Natural Science Foundation of China under Grant No. 61273285
文摘Crowded scene analysis is currently a hot and challenging topic in computer vision field. The ability to analyze motion patterns from videos is a difficult, but critical part of this problem. In this paper, we propose a novel approach for the analysis of motion patterns by clustering the tracklets using an unsupervised hierarchical clustering algorithm, where the similarity between tracklets is measured by the Longest Common Subsequences. The tracklets are obtained by tracking dense points under three effective rules, therefore enabling it to capture the motion patterns in crowded scenes. The analysis of motion patterns is implemented in a completely unsupervised way, and the tracklets are clustered automatically through hierarchical clustering algorithm based on a graphic model. To validate the performance of our approach, we conducted experimental evaluations on two datasets. The results reveal the precise distributions of motion patterns in current crowded videos and demonstrate the effectiveness of our approach.
文摘We previously proposed a method for creating product maps with SOM （Self-Organizing Maps） to be used during purchase decision making. In that study, we first established two class boundaries, which divide the area between the minimum and maximum range of an input feature value into three equal parts. Then, we produced self-organizing product maps using classification data inputs. Finally, we applied our method to five product types and confirmed its effectiveness. In this paper, we propose a method for selecting alternatives from a product map, in which we have located a favorite several examples of selecting alternatives and making decisions using cluster, and/or from a favorite component map. We then show the AHP （Analytic Hierarchy Process）.
基金Supported by Grant from the Administration of Traditional Chinese Medicine of Guangdong Province in China(No.20131161)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20124425110004)
文摘OBJECTIVE: To analyze the component law of Chinese medicines in fuming-washing therapy for knee osteoarthritis(KOA), and develop new fuming-washing prescriptions for KOA through unsupervised data mining methods.METHODS: Chinese medicine recipes for fuming-washing therapy for KOA were collected and recorded in a database. The correlation coefficient among herbs, core combinations of herbs, andnew prescriptions were analyzed using modified mutual information, complex system entropy cluster, and unsupervised hierarchical clustering, respectively.RESULTS: Based on analysis of 345 Chinese medicine recipes for fuming-washing therapy, 68 herbs occurred frequently, 33 herb pairs occurred frequently, and 12 core combinations were found.Five new fuming-washing recipes for KOA were developed.CONCLUSION: Chinese medicines for fuming-washing therapy of KOA mainly consist of wind-dampness-dispelling and cold-dispersing herbs, blood-activating and stasis-resolving herbs,and wind-dampness-dispelling and heat-clearing herbs. The treatment of fuming-washing therapy for KOA also includes dispelling wind-dampness and dispersing cold, activating blood and resolving stasis, and dispelling wind-dampness and clearing heat. Zhenzhutougucao(Herba Speranskiae Tuberculatae), Honghua(Flos Carthami), Niuxi(Radix Achyranthis Bidentatae), Shenjincao(Herba Lycopodii Japonici), Weilingxian(Radix et Rhizoma Clematidis Chinensis), Chuanwu(Radix Aconiti), Haitongpi(Cortex Erythrinae Variegatae), Ruxiang(Olibanum),Danggui(Radix Angelicae Sinensis), Caowu(Radix Aconiti Kusnezoffii), Moyao(Myrrha), and Aiye(Folium Artemisiae Argyi) are the main herbs used in the fuming-washing treatment for KOA.
