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2014 4th ACM International Conference on Multimedia Retrieval, ICMR 2014

作者： Xu, Jieping Li, Xirong Hao, Yun Yang, Gang Multimedia Computing Lab. School of Information Renmin University of China Beijing 100872 China Key Lab of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China Graduate School of Library and Information Science University of Illinois at Urbana-Champaign United States

ISBN: (纸本)1595930361

Despite the impressive progress in music emotion recognition, it remains unclear what aspect of a song, i.e., singing voice and accompanied music, carries more emotional information. As an initial attempt to answer the question, we introduce source separation into a standard music emotion recognition system. This allows us to compare systems with and without source separation, and consequently reveal the influence of singing voice and accompanied music on emotion recognition. Classification experiments on a set of 267 songs with *** annotations verify the new finding that source separation improves song music emotion recognition. Copyright is held by the owner/author(s).

关键词： Source separation

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Automatic data distribution in large-scale OLTP applications

International Journal of Database Theory and Application

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International Journal of database Theory and Application 2014年第4期7卷 37-46页

作者： Wang, Xiaoyan Fan, Xu Chen, Jinchuan Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information and Electrical Engineering Ludong University Yantai 264025 China School of Information Renmin University of China Beijing 100872 China

With the dramatic increase of data volume, automatic data distribution has been one of the key techniques and intractable problem for distributed systems. This work summarizes the problem of data distribution and abstracts it as a general triangle model called DaWN. Based on data and workload analysis, it presents a novel strategy called ADDS for automatic data distribution in OLTP applications. According to the results of a series of experiments over TPC-C datasets and transactions, the proposed approach shows effective improvements.© 2014 SERSC.

关键词： data handling

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The research on three-dimensional simulation of forest fire by FARSITE for GIS application

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Energy Education Science and Technology Part A: Energy Science and Research 2014年第5期32卷 3231-3240页

作者： Li, Jian Wei Huang, Shiwu Chen, Chongcheng Xu, Qifeng Fuzhou University and Key Lab of Spatial Data Mining & Information Sharing of MOE Spatial Information Research Center FuzhouFujian China Fzuzhou university and College of Physics and Information Engineering FuzhouFujian China

Wildfire spread is a complex process affected by many elements. FARSITE (Fire Area Simulator) is a forest fire spread simulation system widely applied and recognized in the world. This paper briefly describes the principles of the forest fire spread models as well as the instruction and treatment of the data required in FARSITE. The three-dimensional forest fire spread simulation system is then introduced, which uses the OSG (Open Scene Graph) as the three-dimensional graphic engine, the particle system for rendering simulation, and the FARSITE as the calculation engine. The three-dimensional simulation system displays the forest fire spread process in three dimensions, which can be used for predicting the edge of the forest fire and assessing the lose and damage as the burned area, and contributing to a more intuitive understanding of the elements affecting the forest fire spread. © Sila Science. All rights reserved.

关键词： Engines

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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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Renmin University of China at ImageCLEF 2013 scalable concept image annotation

Renmin University of China at ImageCLEF 2013 scalable concep...

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2013 Cross Language Evaluation Forum Conference, CLEF 2013

作者： Li, Xirong Liao, Shuai Liu, Binbin Yang, Gang Jin, Qin Xu, Jieping Du, Xiaoyong Key Lab of Data Engineering and Knowledge Engineering MOE Japan Multimedia Computing Lab School of Information Renmin University of China Zhongguancun Street 59 Beijing100872 China

In this paper we describe our image annotation system par ticipated in the ImageCLEF 2013 scalable concept image annotation task. The system leverages multiple base classifiers, including single feature and multi-feature kNN classifiers and histogram intersection ker nel SVMs, all of which are learned from the provided 250K web images and provided features with no extra manual verification. These base clas sifiers are combined into a stacked model, with the combination weights optimized to maximize the geometric mean of F-samples, F-concepts, and AP-samples metrics on the provided development set. By varying the configuration of the system, we submitted five runs. Evaluation re sults show that for all of our runs, model stacking with optimized weights performs best. Our system can annotate diverse Internet images purely based on the visual content, at the following accuracy level: F-samples of 0.290, F-concepts of 0.304, and AP-samples of 0.380. What is more, a system-to-system comparison reveals that our system and the best sub mission this year are complementary with respect to the best annotated concepts, suggesting the potential for future improvement.

关键词： Image annotation

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Top-k neighborhood dominating query

Top-k neighborhood dominating query

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

作者： Xie, Xike Lu, Hua Chen, Jinchuan Shang, Shuo Department of Computer Science Aalborg University Denmark Key Labs of Data Engineering and Knowledge Engineering MOE Renmin University of China China

ISBN: (纸本)9783642374869

In many real-life applications, spatial objects are associated with multiple non-spatial attributes. For example, a hotel may have price and rating in addition to its geographic location. In traditional spatial databases, spatial objects are often ranked solely based on their distance to a given query location, e.g., in a nearest neighbor search. In another line of research, domination based skyline queries are used to return best objects according to multi-criteria on non-spatial attributes. In this paper, we study how to rank spatial objects with respect to their non-spatial attributes within their spatial neighborhoods. To enable a general ranking, we design a ranking function that inherits the advantages of dominance relationship and integrates them with spatial proximity. Further, we propose an effective index structure, and a branch and bound solution that executes the ranking efficiently via the index. We conduct extensive empirical studies on real and synthetic datasets. The results demonstrate the high efficiency of our proposal compared to straightforward alternatives. © Springer-Verlag 2013.

关键词： Nearest neighbor search

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Efficient SPARQL query evaluation via automatic data partitioning

Efficient SPARQL query evaluation via automatic data partiti...

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

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

ISBN: (纸本)9783642374494

The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like Hadoop is a good choice for processing queries over large data sets. Previous works on evaluating SPARQL queries with Hadoop mainly focus on reducing the number of joins through careful split of HDFS files and algorithms for generating Map/Reduce jobs. However, the way of partitioning RDF data could also affect the performance. Specifically, a good partitioning will greatly reduce or even totally avoid cross-node joins and significantly reduce the cost of query evaluation. Based on HadoopDB, this work processes SPARQL queries in a hybrid architecture where Map/Reduce takes charge of the computing tasks and an RDF query engine, RDF-3X, stores the data and evaluates join operations over local data. Based on analysis of query work-loads, we propose a novel algorithm for automatically partitioning RDF data. We also present an approximate solution to physically place the partitions in order to reduce data redundancy. All the proposed approaches are evaluated by extensive experiments over large RDF data sets. © Springer-Verlag 2013.

关键词： Resource Description Framework (RDF)

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Cross-codebook image classification

Cross-codebook image classification

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14th Pacific-Rim Conference on Multimedia, PCM 2013

作者： Liao, Shuai Li, Xirong Du, Xiaoyong Key Lab of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China Beijing 100872 China State Key Lab of Software Development Environment Beijing 100191 China

ISBN: (纸本)9783319037301

Representing images by bag of visual codes (BoVC) features has been the cornerstone of state-of-the-art image classification system. Since the BoVC features depend on a precomputed codebook in use, when the codebook applied to test images differs from the codebook of an existing image classification system, the system becomes inapplicable. To resolve the codebook incompatibility problem, we propose in this paper cross-codebook image classification. This is achieved by transforming BoVC features derived from one codebook to make them compatible with another codebook. Two BoVC transform methods, i.e., code-reassignment and least squares, are studied. Experiments on a popular image classification benchmark set show that both methods are better than random guess when crossing the codebooks. In particular, when the BoVC features are transformed from a higher dimension to a relatively small dimension, cross-codebook image classification has a similar performance compared to within-codebook image classification, with a relative performance loss of 1.3% only. The results justify the feasibility of the proposed cross-codebook image classification. © Springer International Publishing Switzerland 2013.

关键词： Image classification

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TYG: A tag-as-you-go online annotation tool for web browsing and navigation

TYG: A tag-as-you-go online annotation tool for web browsing...

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6th International Conference on knowledge Science, engineering and Management, KSEM 2013

作者： Hu, He Du, Xiaoyong School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing 100872 China

ISBN: (纸本)9783642397868

We present TYG (Tag-as-You-Go) in this paper, a chrome browser extension for personal knowledge annotation on standard web pages. We investigate an approach to combine a K-Medoid-style clustering algorithm with the user input to achieve semi-automatic web page annotation. The annotation process supports user-defined tagging schema and comprises an automatic mechanism that is built upon clustering techniques, which can group similar html nodes into clusters corresponding to the user specification. TYG is a prototype system illustrating the proposed approach. Experiments with TYG show that our approach can achieve both efficiency and effectiveness in real world annotation scenarios. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Websites

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FARP: Mining fuzzy association rules from a probabilistic quantitative database

FARP: Mining fuzzy association rules from a probabilistic qu...

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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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