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On charactering of information propagation in online social networks

Journal of Networks 2013年第1期8卷 124-131页

作者： Han, Xiaoting Niu, Li School of Economics and Management Beihang University Beijing China Key Laboratory of Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Information Resource Management Renmin University of China Beijing China

Recent years have witnessed the explosive growth of online social networks (OSNs), which provide a perfect platform for observing the information propagation. Based on the theory of complex network analysis, considering each node in OSNs as an agent, an information propagation model called IP-OSN has been proposed in this paper, and numerical simulation experiments have been extensively conducted, which show the mechanism of information propagation in OSNs. It can be seen from the experimental results that along with the information spreading scope will be larger while time passing. Moreover, from the network structure perspective, some interesting findings are got. First, the number of initial known nodes has a certain impact on the information propagation speed;however it doesn't affect the number of final known and unknown nodes. Then, the number of neighbors has a great impact on the information propagation process and results. Finally, percentage of different user type is the decisive factor for information propagation either in final node number or propagation speed. This paper attempts to complement the theoretical framework of information propagation and complex networks, and thus to further promote the practice of information control in OSNs. © 2013 ACADEMY PUBLISHER.

关键词： Social networking (online)

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Summarizing Large-Scale database Schema Using Community Detection

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Journal of Computer Science & Technology 2012年第3期27卷 515-526页

作者：王雪周烜王珊 School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China

Schema summarization on large-scale databases is a challenge. In a typical large database schema, a great proportion of the tables are closely connected through a few high degree tables. It is thus difficult to separate these tables into clusters that represent different topics. Moreover, as a schema can be very big, the schema summary needs to be structured into multiple levels, to further improve the usability. In this paper, we introduce a new schema summarization approach utilizing the techniques of community detection in social networks. Our approach contains three steps. First, we use a community detection algorithm to divide a database schema into subject groups, each representing a specific subject. Second, we cluster the subject groups into abstract domains to form a multi-level navigation structure. Third, we discover representative tables in each cluster to label the schema summary. We evaluate our approach on Freebase, a real world large-scale database. The results show that our approach can identify subject groups precisely. The generated abstract schema layers are very helpful for users to explore database.

关键词： schema summarization large scale community detection

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A broadcasting multiple blind signature scheme based on quantum GHZ entanglement

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International Journal of Modern Physics: Conference Series 2014年第33期ijmpcs卷

作者： Yuan Tian Hong Chen Yan Gao Honglin Zhuang Haigang Lian Zhengping Han Peng Yu Xiangze Kong Xiaojun Wen Key Laboratory of Data Engineering and Knowledge Engineering China (Remin University of China) of Ministry of Education Beijing 100872 China School of Information Renmin University of China Beijing 100872 China China Computer User Association Information Protection Branch Beijing 100089 China School of Computer Science and Engineering Beihang University Beijing 100083 China School of Electronics & Information Engineering Shenzhen Polytechnic Shenzhen 518055 China

Using the correlation of the GHZ triplet states, a broadcasting multiple blind signature scheme is proposed. Different from classical multiple signature and current quantum signature schemes, which could only deliver either multiple signature or unconditional security, our scheme guarantees both by adopting quantum key preparation, quantum encryption algorithm and quantum entanglement. Our proposed scheme has the properties of multiple signature, blindness, non-disavowal, non-forgery and traceability. To the best of our knowledge, we are the first to propose the broadcasting multiple blind signature of quantum cryptography.

关键词： Broadcasting multiple blind signature quantum encryption algorithm quantum entanglement quantum cryptography

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Synonyms weighted LDA for product aspects extraction

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International Journal of Applied Mathematics and Statistics 2013年第24期51卷 283-291页

作者： Peng, Yun Wan, Changxuan School of Information and Technology Jiangxi University of Finance and Economics Nanchang 330013 Jiangxi China Computer and Information Engineering College Jiangxi Normal University Nanchang 330022 Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 Jiangxi China

It is important to extract the aspects from the comments of shoppers about certain products. Product aspect descriptions often contain words of same meaning, and discriminating these synonyms effectively can improve the efficiency of aspects extraction. Standard topic model in identifying those words, because of the absent introduction of priori knowledge, will largely ignore the relations of words meaning. An improved aspects extracting model of LDA by adding synonymous words constraint is proposed in this paper. In the process of words clustering analysis, words with high similarity are aggregated in the same cluster. In the stage of aspects extraction, we introduce words clustering and cluster membership weights as priori knowledge to strengthen the original LDA topic model for features clustering, which can improve the accuracy of product aspects extraction. Our experiments show that synonyms weighted LDA proposed in this paper outperforms the original LDA by a large margin. © 2013 by CESER Publications.

关键词： Extraction

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A new BP algorithm for network marketing performance evaluation of agricultural products

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Journal of Applied Sciences 2013年第20期13卷 4332-4335页

作者： Zou, Chun-Fang Huang, Li-Juan School of of Business Administration Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China School of Information Technology Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China

Network marketing performance evaluation can sum up and improve the network marketing activities for network enterprises. So, how to evaluate network marketing performance has become a matter of concern in the field related. The study mainly takes agricultural products for example and presents a new algorithm for evaluating network marketing performance based on improved BP neural network algorithm. First, a evaluation indicator system for evaluating network marketing performance of agricultural products is constructed;Second the study analyzes the reasons of the defects of BP neural network algorithm and then designs a new BP algorithm and improves it through changing its learning rate to speed up the calculation and simplify the structure of the original BP algorithm;Finally, the improved algorithm is realized with three e_commerce enterprises are taken for examples to evaluate the network marketing performance and verify the validity and feasibility of the model and the experimental results show that the model can evaluate the network marketing performance of different enterprises practically. © 2013 Asian Network for Scientific Information.

关键词： Agricultural products

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A framework for personalized management of domain ontologies

A framework for personalized management of domain ontologies

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2012 IEEE/ACIS 11th International Conference on Computer and Information Science, ICIS 2012

作者： Liu, Runnan Wang, Puwei Zheng, Shixian Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China

ISBN: (纸本)9780769546940

As the sharable and reusable domain knowledge, domain ontology increasingly serves as a foundation for semantic Web. Personalized management of domain ontologies is to provide personalized views of domain ontologies to users during run time according to user preferences. It helps that users can focus on their interested parts, instead of the whole. It increases the efficiency of ontology-based application. This paper proposes a framework for personalized management of domain ontologies. In this framework, a user model firstly is introduced to describe user preferences. Secondly, domain ontologies are decomposed into moderate-scale modules with high cohesion and low coupling. During run time, modules that a user is interested in are selected out based on the user's preferences. Finally, the selected modules are combined to construct personalized views of domain ontologies for the user. © 2012 IEEE.

关键词： Ontology

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An approach for personalized tag recommendation based on interest transfer model

An approach for personalized tag recommendation based on int...

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9th Web Information Systems and Applications Conference, WISA 2012

作者： Liu, Yue Yang, Nan Yang, Gang School of Information Renmin University of China Bejing China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Bejing China

ISBN: (纸本)9781467330541

Recently, social tagging systems become more and more popular in many Web 2.0 applications. In such systems, Users are allowed to annotate a particular resource with a freely chosen a set of tags. These user-generated tags can represent users' interests more concise and closer to human understanding. Interests will change over time. Thus, how to describe users' interests and interests transfer path become a big challenge for personalized recommendation systems. In this approach, we propose a variable-length time interval division algorithm and user interest model based on time interval. Then, in order to draw users' interests transfer path over a specific time period, we suggest interest transfer model. After that, we apply a classical community partition algorithm in our approach to separate users into communities. Finally, we raise a novel method to measure users' similarities based on interest transfer model and provide personalized tag recommendation according to similar users' interests in their next time intervals. Experimental results demonstrate the higher precision and recall with our approach than classical user-based collaborative filtering methods. © 2012 IEEE.

关键词： Collaborative filtering

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JUFE at INEX 2011 Snippet Retrieval Track

JUFE at INEX 2011 Snippet Retrieval Track

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Lecture Notes in Computer Science

作者： Liu, Dexi Wan, Changxuan Liao, Guoqiong Zhong, Minjuan Liu, Xiping School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783642357336

Jiangxi University of Finance and Economics (JUFE) submitted 8 runs to the Snippet Retrieval Track at INEX *** report describes an XML snippet retrieval method based on Average Topic Generalization (ATG) model used by JUFE. The basic idea of the ATG is that different element in an XML document plays different role and hence should has distinguishing importance. The ATG model sets a weight automatically to each element according to its tag or path in the XML document. Then, the BM25EW model based on the ATG is proposed to retrieve and rank the relevant elements in an XML document collection. All windows in the most relevant elements are scored and those windows with higher scores are extracted as snippets. By comparing with the runs under different strategies, the performance are discussed and analyzed in detail. © Springer-Verlag Berlin Heidelberg 2012.

关键词： XML

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FindCredPg: A novel method to find credible pages based on trust web graph

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14th Asia Pacific Web Technology Conference, APWeb 2012

作者： Wang, Teng Zhu, Qing Wang, Shan Liang, Jingfan Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Information Renmin University of China Beijing China

ISBN: (纸本)9783642292521

Finding credible pages is a challenging problem on the Web. Our key observation in this paper is that credible pages usually link to credible content-related pages, which is different from a normal page usually links to normal pages in spam page detection. We propose a novel method to find credible pages based on the trust web graph we define. This method first measures the content correlation between pages connected by hyperlinks, then it combines web link structure with content correlation value of pages to build a trust web graph. At last, credible pages are found successfully by using trust relation of vertices on the trust web graph. We construct a real-world data set by crawling millions of pages on the web and run a set of experiments on this data set. Experiment results show that the accuracy of this method is near 80% and the efficiency is higher. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Hypertext systems

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Summarizing large-scale database schema using community detection

Summarizing large-scale database schema using community dete...

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作者： Wang, Xue Zhou, Xuan Wang, Shan School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China

Schema summarization on large-scale databases is a challenge. In a typical large database schema, a great proportion of the tables are closely connected through a few high degree tables. It is thus dificult to separate these tables into clusters that represent different topics. Moreover, as a schema can be very big, the schema summary needs to be structured into multiple levels, to further improve the usability. In this paper, we introduce a new schema summarization approach utilizing the techniques of community detection in social networks. Our approach contains three steps. First, we use a community detection algorithm to divide a database schema into subject groups, each representing a specific subject. Second, we cluster the subject groups into abstract domains to form a multi-level navigation structure. Third, we discover representative tables in each cluster to label the schema summary. We evaluate our approach on Freebase, a real world large-scale database. The results show that our approach can identify subject groups precisely. The generated abstract schema layers are very helpful for users to explore database. © 2012 Springer Science+Business Media, LLC & Science Press, China.

关键词： database systems

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