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Efficient SPARQL query processing in mapreduce through data partitioning and indexing

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14th Asia Pacific Web Technology Conference, APWeb 2012

作者： Nie, Zhi Du, Fang Chen, Yueguo Du, Xiaoyong Xu, Linhao Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China IBM Research China Beijing China

ISBN: (纸本)9783642292521

Processing SPARQL queries on single node is obviously not scalable, considering the rapid growth of RDF knowledge bases. This calls for scalable solutions of SPARQL query processing over Web-scale RDF data. There have been attempts for applying SPARQL query processing techniques in MapReduce environments. However, no study has been conducted on finding optimal partitioning and indexing schemes for distributing RDF data in MapReduce. In this paper, we investigate RDF data partitioning technique that provides effective indexing schemes to support efficient SPARQL query processing in MapReduce. Our extensive experiments over a huge real-life RDF dataset show the performance of the proposed partitioning and indexing schemes for efficient SPARQL query processing. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： MapReduce

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Improve top-K recommendation by extending review analysis

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14th Asia Pacific Web Technology Conference, APWeb 2012

作者： Zhu, Qing Xing, Zhe Liang, Jingfan School of Information Renmin University of China Beijing 100872 China Key Laboratory for Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642292521

The Web has become the popular place for people to purchase product and acquire services, so collaborative filtering is one of the most important algorithms applied in e-commerce recommendation systems. Unfortunately, it is widely recognized that the traditional recommendation methods are inefficient when the user rating data is extremely sparse. In order to overcome the limitations, good recommendation tools are needed to help Web customers determine the products and satisfaction services. In this paper, we propose a multi-dimensional adaptive recommendation algorithm by extending opinion analysis to improve top-k recommendation. In the first step, the novel algorithm that uses extened opinion analysis, creatively combines three dimensional recommendation models: user-based, item-based and opinion-based collaborative filtering. It successfully integrates opinion mining technology with collaborative filtering algorithm. In the second step, we configured the dynamic measurement would help us determine the weight of three dimensions: user-based, item-based and opinion-based analysis, and hence get the final prediction result. The experimental results show that multi-dimensional recommendation can effectively alleviate the dataset sparsity problem and achieve better prediction accuracy compared to other traditional collaborative recommendation algorithms. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Collaborative filtering

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H-tree: A hybrid structure for confidence computation in probabilistic databases

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14th Asia Pacific Web Technology Conference, APWeb 2012

作者： Zhang, Qian Qin, Biao Wang, Shan Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642292521

Probabilistic database has become a popular tool for uncertain data management. Most work in the area is focused on efficient query processing and has two main directions, accurate or approximate evaluation. In recent work for conjunctive query without self-joins on a tuple-independent probabilistic database, query evaluation is equivalent to computing marginal probabilities of boolean formulas associated with query results. If formulas can be factorized into a read-once form where every variable appears at most once, confidence computation is reduced to a tractable problem that can be evaluated in linear time. Otherwise, it is regarded as a NP-hard problem and need to be evaluated approximately. In this paper, we propose a framework that evaluates both tractable and NP-hard conjunctive queries efficiently. First, we develop a novel structure H-tree, where boolean formulas are decomposed to small partitions which are either read-once or NP-hard. Then we propose algorithms for building H-tree and parallelizing (approximate) confidence computation. We also propose fundamental theorems to ensure the correctness of our approaches. Performance experiments demonstrate the benefits of H-tree, especially for approximate confidence evaluation on NP-hard queries. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Query processing

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Fusing concept detection and geo context for visual search 12

Fusing concept detection and geo context for visual search

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2nd ACM International Conference on Multimedia Retrieval, ICMR 2012

作者： Li, Xirong Snoek, Cees G.M. Worring, Marcel Smeulders, Arnold W.M. MOE Key Lab of Data Engineering and Knowledge Engineering Renmin University of China China Intelligent Systems Lab Amsterdam University of Amsterdam Netherlands Centrum Wiskunde and Informatica Netherlands

ISBN: (纸本)9781450313292

Given the proliferation of geo-tagged images, the question of how to exploit geo tags and the underlying geo context for visual search is emerging. Based on the observation that the importance of geo context varies over concepts, we propose a concept-based image search engine which fuses visual concept detection and geo context in a concept-dependent manner. Compared to individual content-based and geo-based concept detectors and their uniform combination, concept-dependent fusion shows improvements. Moreover, since the proposed search engine is trained on social-tagged images alone without the need of human interaction, it is flexible to cope with many concepts. Search experiments on 101 popular visual concepts justify the viability of the proposed solution. In particular, for 79 out of the 101 concepts, the learned weights yield improvements over the uniform weights, with a relative gain of at least 5% in terms of average precision. Copyright © 2012 ACM.

关键词： Search engines

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Predicting retweet behavior in Weibo social network

Predicting retweet behavior in Weibo social network

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13th International Conference on Web Information Systems engineering, WISE 2012

作者： Zhang, Hongbo Zhao, Qun Liu, Hongyan Xiao, Ke He, Jun Du, Xiaoyong Chen, Hong Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China School of Economics and Management Tsinghua University China

ISBN: (纸本)9783642350627

Retweeting ensures the information diffusion in micro-blog services. By this simple way, it is convenient for a user to share and spread interesting information in the whole network. In this paper, we consider many features to compute the probability that a user retweets a tweet. With the probability, we build a retweet model to predict the number of possible-views of a tweet. The model is based on the theory of random walks. Experiments conducted on real dataset show that the proposed method has a good performance than the traditional prediction methods. © 2012 Springer-Verlag.

关键词： Forecasting

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Location selection for utility maximization with capacity constraints 12

Location selection for utility maximization with capacity co...

引用

21st ACM International Conference on Information and knowledge Management, CIKM 2012

作者： Sun, Yu Huang, Jin Chen, Yueguo Zhang, Rui Du, Xiaoyong School of Information Renmin University of China Beijing China University of Melbourne Melbourne VIC Australia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China

ISBN: (纸本)9781450311564

Given a set of client locations, a set of facility locations where each facility has a service capacity, and the assumptions that: (i) a client seeks service from its nearest facility;(ii) a facility provides service to clients in the order of their proximity, we study the problem of selecting all possible locations such that setting up a new facility with a given capacity at these locations will maximize the number of served clients. This problem has wide applications in practice, such as setting up new distribution centers for online sales business and building additional base stations for mobile subscribers. We formulate the problem as location selection query for utility maximization. After applying three pruning rules to a baseline solution,we obtain an efficient algorithm to answer the query. Extensive experiments confirm the efficiency of our proposed algorithm. © 2012 ACM.

关键词： Location

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Fuzzy Rough Based Decision Tree Constructing

Fuzzy Rough Based Decision Tree Constructing

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第十二届中国Rough集与软计算学术会议、第六届中国Web智能学术研讨会及第六届中国粒计算学术研讨会联合学术会议

作者： CHEN Wei ZHAO Su-yun CHEN Hong LI Cui-ping Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of ChinaMOE Beijin Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of ChinaMOE Beijin

Decision tree and fuzzy rough set are two distinct but complementary *** tree is a simple and easy-understandable rule-based classifier,whereas the tool of fuzzy rough sets are effective on attribute and sample *** is promising to propose an approach to integrate these two rule based classification tools to construct a novel decision tree based on fuzzy rough *** this paper,based on the basic concept of fuzzy rough sets,i.e.,consistence degree,we propose a fuzzy rough decision tree which is completely different from the existing classification *** three key basic elements of decision tree,i.e.,node,branch and leaf,are designed in a new way by using the notions in fuzzy rough *** then one algorithm to build fuzzy rough tree classifier is ***,experimental results show that the proposed algorithm is readily comprehensible and effective.

关键词： Fuzzy rough sets Decision tree Consistence degree Rule-based classifier

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Radical features for Chinese text classification

Radical features for Chinese text classification

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International Conference on Fuzzy Systems and knowledge Discovery (FSKD)

作者： He Hu Xiaoyong Du Key Laboratories of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China

Chinese radicals play important roles in forming Chinese character's semantic meaning. The semantic properties of radicals make them a promising source of information to be analyzed in text mining and content extraction. However, until recently there is little research work concentrating on using the radical set in text mining related tasks. We investigate the roles of radicals in Chinese text classification tasks. In the task, texts are transformed into vectors of radicals, characters and words. Radicals are further pruned by their semantic strengths and network traits. We carry out experiments with real data from Open Directory Project. The experiments results justify Chinese radicals as important features for semantic processing in Chinese text mining tasks.

关键词： Europe Positron emission tomography Education Vectors

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Combining N-gram retrieval with weights propagation on massive RDF graphs

Combining N-gram retrieval with weights propagation on massi...

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International Conference on Fuzzy Systems and knowledge Discovery (FSKD)

作者： He Hu Xiaoyong Du School of Information Renmin University of China Beijing China Key Laboratories of Data Engineering and Knowledge Engineering Ministry of Education China

N-gram approach takes the position information into account additionally and thus can offer higher accuracy in query answering than keyword based approaches and is widely used in IR and NLP. However, in large-scale RDF graphs, URIs instead of documents are the ranking and querying units; URIs are usually much shorter than documents, and different URIs are interlinked into a massive network. One shot n-gram querying is usually not good for the RDF data in many cases. In this paper, we present a hybrid framework which combines the n-gram retrieval with link analysis based weight propagation. The idea is to exploit the link structures in the RDF data graphs and propagate the one shot n-gram score weights along with these links. Large scale experiments using MapReduce on Billion Triples Challenge dataset show the hybrid framework achieves an 80.3% improvement in relevance scores over mere n-gram retrieval.

关键词： Resource description framework Semantics Conferences Educational institutions Legged locomotion Indexes USA Councils

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A Comparative Analysis of knowledge Management Methods in the Three knowledge Management Standards

A Comparative Analysis of Knowledge Management Methods in th...

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2012年管理与服务科学国际会议(MASS 2012)

作者： Shaotong Xu Xiaomi An Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China) MOE

This paper aims to identify knowledge management (KM) methods that have been used in three KM Standards, i.e. KM Standards of Britain, European Union(EU) and Australia, with comparative analysis of three KM issues covering: basic definitions, KM work processes, essential factors and management frameworks;with a chronological analysis of their characteristics and evolution. The studies find that along with the practical development of KM practices, concepts of KM are getting understood more and more broadly, ranges of KM activities are extending, but management factors are getting highly integrated, and the management frameworks are going towards ecosystem. The paper provides valuable insight on theoretical and practical development of knowledge management methods and standards.

关键词： knowledge management knowledge management method knowledge management standard

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