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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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Validation of FLUKA code estimation for the production of 63Zn and 65Zn in the Cu target for low energy proton accelerator

Validation of FLUKA code estimation for the production of 63...

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7th International Symposium on Radiation Safety and Detection Technology(第七届国际声辐射安全与检测技术研讨会)(ISORD-7)

作者： Rui QIU Liu Yuanyuan Hui Zhang Yuxi PAN Wenqian LI Shilian WANG Junli LI Key Laboratory of Particle & Radiation Imaging Ministry of Education Key Laboratory of High Energy Radiation Imaging Fundamental Science Department of Engineering Physics Tsinghua University Beijing 100084 China Nuclear and Radiation Safety Center Ministry of Environmental Protection of P.R.China Beijing 100082 China CTBT Beijing National Data Centre and Radionuclide Laboratory Beijing 100085 China

The medical proton accelerators with energy typically between 10 and 18 MeV have been widely *** induced radioactivity is one of the essential problems in the radiation protection field for the accelerators.

关键词： activation analysis experiment cross section measurement induced radioactivity FLUKA copper target

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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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2012 9th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2012

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

ISBN: (纸本)9781467300223

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. © 2012 IEEE.

关键词： MapReduce

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Extracting domain-relevant term using wikipedia based on random walk model

Extracting domain-relevant term using wikipedia based on ran...

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7th ChinaGrid Annual Conference, ChinaGrid 2012

作者： Wu, Wenjuan Liu, Tao Hu, He Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China

ISBN: (纸本)9780769548166

In this paper we present a new approach for the automatic identification of domain-relevant concepts and entities of a given domain using the category and page structures of the Wikipedia in a language independent way. By applying Markov random walk algorithm on the weighted Wikipedia link graph, our approach can identify large quantities of domain-relevant concepts and entities with very little human effort. Experimental results show that our method achieves high accuracy and acceptable efficiency in domainrelevant term extraction. © 2012 IEEE.

关键词： Markov processes

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Radical features for Chinese text classification

Radical features for Chinese text classification

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2012 9th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2012

作者： Hu, He Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Infonnation Renmin University of China Beijing China

ISBN: (纸本)9781467300223

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. © 2012 IEEE.

关键词： Semantics

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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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Multiple Vehicle-like Target Tracking Based on the Velodyne LiDAR *

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IFAC Proceedings Volumes 2013年第10期46卷 126-131页

作者： Liang Zhang Qingquan Li Ming Li Qingzhou Mao Andreas Nüchter State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan Hubei 430079 China Shenzhen Key Laboratory of Spatial-temporal Smart Sensing and Services Shenzhen University Shenzhen Guangdong 518052 China Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application Ministry of Education of China Wuhan University Wuhan Hubei 430079 China Automation and Machine Vision Group Jacobs University Bremen 28759 Germany

This paper proposes a novel multiple vehicle-like target tracking method based on a Velodyne HDL64E light detection and ranging (LiDAR) system. The proposed method combines multiple hypothesis tracking (MHT) algorithm with dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurately the pose of the ego-vehicle for the transformation of raw measurements taken in the moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.

关键词： Multi-Target Tracking Velodyne Lidar Multiple Hypothesis Tracking Dynamic Point Cloud Registration

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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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Co-spatial searcher: Efficient tag-based collaborative spatial search on geo-social network

Co-spatial searcher: Efficient tag-based collaborative spati...

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17th International Conference on database Systems for Advanced Applications, DASFAA 2012

作者： Zhang, Jinzeng Meng, Xiaofeng Zhou, Xuan Liu, Dongqi School of Information Renmin University of China Beijing China Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9783642290374

The proliferation of geo-social network, such as Foursquare and Facebook Places, enables users to generate location information and its corresponding descriptive tags. Using geo-social networks, users with similar interests can plan for social activities collaboratively. This paper proposes a novel type of query, called Tag-based top-k Collaborative Spatial (TkCoS) query, for users to make outdoor plans collaboratively. This type of queries aim to retrieve groups of geographic objects that can satisfy a group of users' requirements expressed in tags, while ensuring that the objects be within the minimum spatial distance from the users. To answer TkCoS queries efficiently, we introduce a hybrid index structure called Spatial-Tag R-tree (STR-tree), which is an extension of the R-tree. Based on STR-tree, we propose a query processing algorithm that utilizes both spatial and tag similarity constraints to prune search space and identify desired objects quickly. Moreover, a differential impact factor is adopted to fine-tune the returned results in order to maximize the users' overall satisfaction. Extensive experiments on synthetic and real datatsets validate the efficiency and the scalability of the proposed algorithm. © 2012 Springer-Verlag.

关键词： Forestry

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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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