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作者： Pei, Bin Zhao, Suyun Chen, Hong Zhou, Xuan Chen, Dingjie Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

Current studies on association rule mining focus on finding Boolean/quantitative association rules from certain databases or Boolean association rules from probabilistic databases. However, little work on mining association rules from probabilistic quantitative databases has been mentioned because the simultaneous measurement of quantitative information and probability is difficult. By introducing a novel Shannon-like Entropy, we aggregate and measure the information contained in an item with the coexistence of fuzzy uncertainty hidden in quantitative values and random uncertainty. We then propose Support and Confidence metrics for a fuzzy-probabilistic database to quantify association rules. Finally, we design an algorithm, called FARP (mining Fuzzy Association Rules from a Probabilistic quantitative data), to discover frequent fuzzy-probabilistic itemsets and fuzzy association rules using the proposed interest measures. The experimental results show the effectiveness of our method and its practicality in real-world applications. © 2013 Elsevier Inc. All rights reserved.

关键词： Entropy

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On charactering of information propagation in online social networks

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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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ASAWA: An automatic partition key selection strategy

ASAWA: An automatic partition key selection strategy

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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Wang, Xiaoyan Chen, Jinchuan Du, Xiaoyong School of Information Renmin University of China China School of Information and Electrical Engineering Ludong University China Key Laboratory of Data Engineering and Knowledge Engineering MOE China

ISBN: (纸本)9783642374005

With the rapid increase of data volume, more and more applications have to be implemented in a distributed environment. In order to obtain high performance, we need to carefully divide the whole dataset into multiple partitions and put them into distributed data nodes. During this process, the selection of partition key would greatly affect the overall performance. Nevertheless, there are few works addressing this topic. Most previous projects on data partitioning either utilize a simple strategy, or rely on a commercial database system, to choose partition keys. In this work, we present an automatic partition key selection strategy called ASAWA. It chooses partition keys according to the analysis on both dataset and workload schemas. In this way, intimate tuples, i.e. co-appearing in queries frequently, would be probably put into the same partition. Hence the cross-node joins could be greatly reduced and the system performance could be improved. We conduct a series of experiments over the TPC-H datasets to illustrate the effectiveness of the ASAWA strategy. © 2013 Springer-Verlag.

关键词： data handling

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Fast SimRank computation over disk-resident graphs

Fast SimRank computation over disk-resident graphs

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18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Zhang, Yinglong Li, Cuiping Chen, Hong Sheng, Likun Key Lab of Data Engineering and Knowledge Engineering of Ministry of Education And Department of Computer Science Renmin University of China China JiangXi Agricultural University China

ISBN: (纸本)9783642374494

There are many real-world applications based on similarity between objects, such as clustering, similarity query processing, information retrieval and recommendation systems. SimRank is a promising measure of similarity based on random surfers model. However, the computational complexity of SimRank is high and several optimization techniques have been proposed. In the paper optimization issue of Sim-Rank computation in disk-resident graphs is our primary focus. First we suggest a new approach to compute *** we propose optimization techniques that improve the time cost of the new approach from O (kN2 D2) to O (kNL), where k is the number of iteration, N is the number of nodes, L is the number of edges, and D is the average degree of nodes. Meanwhile, a threshold sieving method is presented to reduce storage and computational cost. On this basis, an external algorithm computing SimRank in disk-resident graphs is introduced. In the experiments, our algorithm outperforms its opponent whose computation complexity also is O (kNL). © Springer-Verlag 2013.

关键词： Search engines

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Cluster labeling extraction and ranking feature selection for high quality XML pseudo relevance feedback fragments set

Cluster labeling extraction and ranking feature selection fo...

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9th International Conference on Advanced data Mining and Applications, ADMA 2013

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

ISBN: (纸本)9783642539169

In traditional pseudo feedback, the main reason of the topic drift is the low quality of the feedback source. Clustering search results is an effective way to improve the quality of feedback set. For XML data, how to effectively perform clustering algorithm and then identify good xml fragments from the clustering results is a intricate problem. This paper mainly focus on the latter problem. Based on k-mediod clustering results, This work firstly proposes an cluster label extraction method to select candidate relevant clusters. Secondly, multiple ranking features are introduced to assist the related xml fragments identification from the candidate clusters. Top N fragments compose the high quality pseudo feedback set finally. Experimental results on standard INEX test data show that in one hand, the proposed cluster label extraction method could obtain proper cluster key terms and lead to appropriate candidate cluster selection. On the other hand, the presented ranking features are beneficial to the relevant xml fragments identification. The quality of feedback set is ensured. © 2013 Springer-Verlag.

关键词： Clustering algorithms

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Reflection on the popularity of MapReduce and observation of its position in a unified big data platform

Reflection on the popularity of MapReduce and observation of...

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14th International Conference on Web-Age Information Management, WAIM 2013

作者： Qin, Xiongpai Qin, Biao Du, Xiaoyong Wang, Shan MOE Key Lab. of Data Engineering and Knowledge Engineering Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642395260

In recent years MapReduce has risen to be the de-facto tool for big data processing. MapReduce is a disruptive innovation. It has changed the landscape of database market, the landscape of technologies, as well as the landscape of saying power. The article will give a reflection on the popularity of the technique and some observations of its position in a unified big data platform. © 2013 Springer-Verlag.

关键词： MapReduce

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Mining user interests from information sharing behaviors in social media

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17th Pacific-Asia Conference on knowledge Discovery and data Mining, PAKDD 2013

作者： Wang, Tingting Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374555

Mining user interests and preference plays an important role for many applications such as information retrieval and recommender systems. This paper intends to study how to infer interests for new users and inactive users from social media. Although some recently proposed methods can mine user interests efficiently, these works cannot make full use of relationship between users in their social network. In this paper, we propose a novel approach to infer interests of new users or inactive users based on social connections between users. A random-walk based mutual reinforcement model combining both text and link information is developed in the approach. More importantly, we compare the contribution of different social connections such as "follow", "retweet", "mention", and "comment" to interest sharing. Experiments conducted on real dataset show that our method is effective and outperforms existing algorithms, and different social connections have different impacts on mining user interests. © Springer-Verlag 2013.

关键词： Recommender systems

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MFSV: A truthfulness determination approach for fact statements

MFSV: A truthfulness determination approach for fact stateme...

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18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Wang, Teng Zhu, Qing Wang, Shan 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)9783642374494

How to determine the truthfulness of a piece of information becomes an increasingly urgent need for users. In this paper, we propose a method called MFSV, to determine the truthfulness of fact statements. We first calculate the similarity between a piece of related information and the target fact statement and capture the credibility ranking of the related information through combining importance ranking and popularity ranking. Based on these, contributions of a piece of related information to the truthfulness determination is derived. Then we propose two methods to determine the truthfulness of the target fact statement. At last, we run comprehensive experiments to show MFSV's availability and high accuracy. © Springer-Verlag 2013.

关键词： Computers

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Multi-verifier: A novel method for fact statement verification

Multi-verifier: A novel method for fact statement verificati...

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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

ISBN: (纸本)9783642374005

Untruthful information spreads on the web, which may mislead users or have a negative impact on user experience. In this paper, we propose a method called Multi-verifier to determine the truthfulness of a fact statement. The basic idea is that whether a fact statement is truthful or not depends on the information related to the fact statement. We utilize a popular search engine to collect the top-n search results that are most related to the target fact statement. We then propose support score to measure the extent to which a search result supports the fact statement, and we make use of credibility ranking to rank the search results. At last, we combine the support score and credibility ranking value of a search result to evaluate its contribution to a fact statement determination. Based on the contributions of the search results, we determine the fact statement. Our proposals are evaluated by experiments and results show availability and high precision of the proposed method. © 2013 Springer-Verlag.

关键词： Search engines

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Detecting event rumors on Sina Weibo automatically

Detecting event rumors on Sina Weibo automatically

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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Sun, Shengyun Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374005

Sina Weibo has become one of the most popular social networks in China. In the meantime, it also becomes a good place to spread various spams. Unlike previous studies on detecting spams such as ads, pornographic messages and phishing, we focus on identifying event rumors (rumors about social events), which are more harmful than other kinds of spams especially in China. To detect event rumors from enormous posts, we studied the characteristics of event rumors and extracted features which can distinguish rumors from ordinary posts. The experiments conducted on real dataset show that the new features are effective to improve the rumor classifier. Further analysis of the event rumors reveals that they can be classified into 4 different types. We propose an approach for detecting one major type, text-picture unmatched event rumors. The experiment demonstrates that this approach is well-performed. © 2013 Springer-Verlag.

关键词： Social networking (online)

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