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检索条件"机构=MOE Key Lab. of Data Engineering and Knowledge Engineering"

共 56 条记录，以下是11-20 订阅

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Ontology hierarchies matching by lattices alignment

Ontology hierarchies matching by lattices alignment

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2nd International Workshop on Ontology Matching, OM-2007 - Collocated with the 6th International Semantic Web Conference, ISWC-2007 and the 2nd Asian Semantic Web Conference, ASWC-2007

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

Ontology matching determines the correspondences between concepts and relations of related ontologies. In this paper, we put forward an ontology hierarchies matching approach based on lattices alignment. The proposed lattice-based matching algorithm can be utilized not only in matching processes between two ontologies, but also in annotation processes between an ontology and its corresponding resources. Experiments on spatiotemporal ontology annotation have been carried out which shown the applicability of the approach.

关键词： Ontology

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Integrated retrieval over structured and unstructured data

Integrated retrieval over structured and unstructured data

引用

2012 Cross Language Evaluation Forum Conference, CLEF 2012

作者： Wang, Qiuyue Kang, Jinglin School of Information Renmin University of China Beijing100872 China Key Lab of Data Engineering and Knowledge Engineering MOE Beijing100872 China

We report our experiment results on the INEX 2012 Linked data Track. We participated in the ad hoc and jeopardy tasks. As the new data collection on INEX 2012 Linked data Track features a combination of unstructured and structured data, our first attempt is to investigate different strategies of combining the retrievals over structured and unstructured data, and compare the combined approaches with the traditional unstructured ones. In this paper, we discussed three types of combination strategies and we experimented two of them on the track. The experiment results show that.

关键词： Linked data

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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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Renmin University of China at ImageCLEF 2013 scalab.e 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 scalab.e 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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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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A collab.rative join scheme on a MIC-based heterogeneous platform

A collaborative join scheme on a MIC-based heterogeneous pla...

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Lecture Notes in Computer Science

作者： Zhou, Kailai Sun, Hui Chen, Hong Wu, Tianzhen Li, Cuiping Key Lab of Data Engineering and Knowledge Engineering of MOE School of Information Renmin University of China Beijing China School of Computer and Information Southwest Forestry University Kunming China

ISBN: (纸本)9783319458168

Join is one of the most important operations in data analytics systems. Prior works focus mainly on join optimization using GPUs, but little is known about performance impact on the MICs. In order to investigate potential benefits of the use of MIC accelerators in improving performance of join operation, in this paper we design a join scheme with a CPU and MICs working collab.ratively. This scheme includes task partitioning, a data transfer mode, join algorithm design. Experimental results show that our collective join scheme is effective for a heterogeneous platform with two Xeon Phi cards, and can improve performance by up to 30 % over the CPU-only platform. © Springer International Publishing Switzerland 2016.

关键词： data transfer

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Overview of the INEX 2011 data-centric track

Overview of the INEX 2011 data-centric track

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Lecture Notes in Computer Science

作者： Wang, Qiuyue Ramírez, Georgina Marx, Maarten Theobald, Martin Kamps, Jaap School of Information Renmin University of China China Key Lab. of Data Engineering and Knowledge Engineering MOE China Universitat Pompeu Fabra Spain University of Amsterdam Netherlands Max-Planck-Institut für Informatik Germany

ISBN: (纸本)9783642357336

This paper presents an overview of the INEX 2011 data-Centric Track. Having the ad hoc search task running its second year, we introduced a new task, faceted search task, whose goal is to provide the infrastructure to investigate and evaluate different techniques and strategies of recommending facet-values to aid the user to navigate through a large set of query results and quickly identify the results of interest. The same IMDB collection as last year was used for both tasks. A total of 9 active participants contributed a total of 60 topics for both tasks and submitted 35 ad hoc search runs and 13 faceted search runs. A total of 38 ad hoc search topics were assessed, which included 18 subtopics for 13 faceted search topics. We discuss the setup for both tasks and the results obtained by their participants. © Springer-Verlag 2012.

关键词： XML

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Parallel SimRank computation on large graphs with iterative aggregation

Parallel SimRank computation on large graphs with iterative ...

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16th ACM SIGKDD International Conference on knowledge Discovery and data Mining, KDD-2010

作者： He, Guoming Feng, Haijun Li, Cuiping Chen, Hong Key Lab. of Data Engineering and Knowledge Engineering of Ministry of Education China Department of Computer Science Renmin University of China China No. 59 Zhongguancun Street Haidian District Beijing China

ISBN: (纸本)9781450300551

Recently there has been a lot of interest in graph-based analysis. One of the most important aspects of graph-based analysis is to measure similarity between nodes in a graph. SimRank is a simple and influential measure of this kind, based on a solid graph theoretical model. However, existing methods on SimRank computation suffer from two limitations: 1) the computing cost can be very high in practice;and 2) they can only be applied on static graphs. In this paper, we exploit the inherent parallelism and high memory bandwidth of graphics processing units (GPU) to accelerate the computation of SimRank on large graphs. Furthermore, based on the observation that SimRank is essentially a first-order Markov Chain, we propose to utilize the iterative aggregation techniques for uncoupling Markov chains to compute SimRank scores in parallel for large graphs. The iterative aggregation method can be applied on dynamic graphs. Moreover, it can handle not only the link-updating problem but also the node-updating problem. Extensive experiments on synthetic and real data sets verify that the proposed methods are efficient and effective. © 2010 ACM.

关键词： Graphics processing unit

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Probabilistic range queries for Uncertain Trajectories on road networks 11

Probabilistic range queries for Uncertain Trajectories on ro...

引用

14th International Conference on Extending database Technology: Advances in database Technology, EDBT 2011

作者： Zheng, Kai Trajcevski, Goce Zhou, Xiaofang Scheuermann, Peter School of ITEE University of Queensland Australia Department of EECS Northwestern University United States School of Information Renmin University of China Key Lab. of Data Engineering and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9781450305280

Trajectories representing the motion of moving objects are typically obtained via location sampling, e.g. using GPS or road-side sensors, at discrete time-instants. In-between consecutive samples, nothing is known about the whereabouts of a given moving object. Various models have been proposed (e.g., sheared cylinders;spacetime prisms) to represent the uncertainty of the moving objects both in unconstrained Euclidian space, as well as road networks. In this paper, we focus on representing the uncertainty of the objects moving along road networks as time-dependent probability distribution functions, assuming availab.lity of a maximal speed on each road segment. For these settings, we introduce a novel indexing mechanism - UTH (Uncertain Trajectories Hierarchy), based upon which efficient algorithms for processing spatio-temporal range queries are proposed. We also present experimental results that demonstrate the benefits of our proposed methodologies.

关键词： Trajectories

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Efficient Computation of Reverse Skyline on data Stream

Efficient Computation of Reverse Skyline on Data Stream

引用

The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

作者： Ling Zhu Cuiping Li Hong Chen School of Information Renmin University of China Key Lab of Data Engineering and Knowledge Engineering of MOE

Reverse Skyline Queries have been proved very useful in business location, environmental monitoring and some other applications. In this paper, we consider reverse skyline queries processing on data stream, which provides continuous, high-speed data elements. Specifically, we consider the latest objects in the sliding window. The challenge is that it is difficult to maintain a multidimensional index (for example, R-tree) in a dynamic dataset. Focusing on this challenge, we propose an algorithm with a DC-Tree as index and effective pruning methods to reduce the search space of query processing and the cost of index maintaining. Extensive experiments show that our algorithms are efficient and effective for on-line reverse skyline query.

关键词： Monitoring Query processing Costs data engineering knowledge engineering Multidimensional systems

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