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检索条件"机构=Key Lab of Data Engineering and Knowledge Engineering of MOE Renmin University of China"

共 296 条记录，以下是131-140 订阅

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DSOSW: A Deleting Strategy in Mining Frequent Itemsets over Sliding Window of Stream

DSOSW: A Deleting Strategy in Mining Frequent Itemsets over ...

引用

International Symposiums on Information Processing (ISIP)

作者： Haifeng Li Hong Chen Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China Renmin University of China Beijing CN

Most traditional mining approaches of frequent item sets consider mainly on databases and thus can use the second storage and need multiple scans which are not adapted to mining of stream. Some new algorithms over stream's sliding window are presented recently, which perform addition and deletion over stream independently, so the common deleting strategy which removes the earliest transaction is used when the window slides. This paper considers both operations together to reduce the computation cost, consequently, three deleting strategies are proposed to improve the performance with little precision loss. The experimental results show that these strategies over current method are effective and efficient.

关键词： data mining Itemsets Writing laboratories data engineering knowledge engineering Transaction databases Information processing Computational efficiency Performance loss

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VANETs-Based Real-time Traffic data Dissemination

VANETs-Based Real-time Traffic Data Dissemination

引用

2010 IEEE International Conference Conferenhce on Wireless Communications,Networking and Information Security(2010 IEEE 无线通信、网络技术与信息安全国际会议 WCNIS)

作者： Wenping Chen Department of Computer Science??Renmin University of China Beijing Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE

ISBN: (纸本)9781424458509

Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by leveraging the techniques of Vehicular Ad hoc Networks (VANETs) we present a real-time abnormal traffic data dissemination protocol. Specifically, all vehicles running on the same road segment are regarded as a cluster to generate traffic message about this segment. To reduce communication cost, only abnormal traffic data is issued and spread to nearby road segments. By employing event-driven and period combined mechanism, the abnormal traffic messages are disseminated to the vehicles that probably need the messages in time. We propose a distance dependent forwarder selection method to disseminate traffic message. When transmitted inside a cluster, messages are forwarded along the segment from one end to the other based on the least hops principle;while transmitted among clusters, messages are transmitted in epidemic routing mode, which ensure the fast and reliable dissemination. To evaluate the performance of our protocol, we use the real traffic data of Beijing at peak hour. The simulation results demonstrate that our protocol is feasible and efficient for metropolitan-size city.

关键词： vehicular networks traffic real-time

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A Parallel Recovery Scheme for Update Intensive Main Memory database Systems

A Parallel Recovery Scheme for Update Intensive Main Memory ...

引用

IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Xiongpai Qin Yanqin Xiao Wei Cao Shan Wang Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing P.R. China

In update intensive applications, main memory database systems produce large volume of log records, it is critical to write out the log records efficiently to speedup transaction processing. We propose a parallel recovery scheme based on XOR differential logging for main memory database systems in such environments. Some NVRAM is used to temporarily hold log records and decouple transaction committing from disk writes, inherited parallelism properties of differential logging are exploited to accelerate log flushing by using multiple log disks. During recovery, log records are loaded from multiple log disks and applied to data partition in time without the need of reordering according to serialization order, total recovery time is cut down. The scheme employs a data partition based consistent checkpointing method. The log records are classified according to IDs of data partitions accessed. data partitions are recovered according to loading priorities computed from update frequencies and transaction waiting times, data access demands of new transactions coming after failure recovery are given attention immediately, thus the scheme provides system availability during recovery, which is of importance for large scale main memory database systems.

关键词： database systems data engineering Large-scale systems Random access memory Checkpointing Communication industry Defense industry Distributed computing laboratories knowledge engineering

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An Economic Semantic Web Platform

An Economic Semantic Web Platform

引用

International Conference on Grid and Cooperative Computing Workshops (GCCW)

作者： Xiaoyong Du He Hu Man Li Wenjuan Wu Guo Qin Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China Beijing China

The paper describes an ongoing project which implements a subject-oriented semantic Web platform at renmin Univ. of china. The economic semantic Web platform (ESWP) contains three components: collaborative ontology developing environment and repository system (CODERS); economic ontology annotation Web services (ConAnnotator); economic ontology and annotated resources. We describe each of these components in detail and illustrate some use cases of the ESWP

关键词： Semantic Web Ontologies Environmental economics Web services Collaboration Humans Software agents Application software Helium laboratories

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Competition-based Clustering and Energy-Saving data Gathering in wireless sensor networks

Competition-based Clustering and Energy-Saving Data Gatherin...

引用

IET International Conference on Wireless Sensor Network 2010, IET-WSN 2010

作者： Mo, Shangfeng Chen, Hong School of Information Renmin University of China Beijing China Key Lab Data Engn. and Knowledge Engn. MOE Beijing China School of Math and Computer Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9781849192392

A large-scale wireless sensor network can be deployed for a specific application. In such a network, the designed routing algorithms trend to reduce the energy consumption and extend the network lifetime, because the energy is highly limited. To achieve this goal, we proposed a Competition-based Clustering and Energy-saving data Gathering (CCEDG) protocol. The CCEDG consists of two parts: one part is the intra-cluster communication algorithm, another part is the inter-cluster communication algorithm. In phase I of the intra-cluster communication part, we introduce a competitionbased clustering algorithm. Cluster heads with less residual energy than the average residual energy of all nodes in the network have smaller cluster sizes, thus they can preserve more energy. In phase II of the intra-cluster communication part, each member node tries to find a near neighbor node within the same cluster to set up a data relay link, most member nodes use data relay links to communicate with cluster heads, as the communication distance decrease, more energy saved. In our scheme, it is no longer need the help of GPS or other means. Simulation results show that the scheme achieves a significant amount of energy-savings and obtains an obvious improvement on the network lifetime.

关键词： Energy conservation

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Optimizing Random Access to Hierarchically-Compressed data on GPU

Optimizing Random Access to Hierarchically-Compressed Data o...

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Supercomputing Conference

作者： Feng Zhang Yihua Hu Haipeng Ding Zhiming Yao Zhewei Wei Xiao Zhang Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering (MOE) School of Information Renmin University of China Beijing China

ISBN: (纸本)9781665454452

GPU's powerful computational capacity holds great potentials for processing hierarchically-compressed data without decompression in data science domain. Unfortunately, existing GPU approaches offer only traversal-based data analytics; random access is extremely inefficient, substantially limiting their utility. To solve this problem, we develop a novel and broadly applicable optimization that enables efficient random access to hierarchically-compressed data without decompression in GPU memory. We address three major challenges for enabling efficient random access to compressed data on GPUs. The first challenge is designing GPU data structures that support random access. The second challenge is efficiently generating data structures on GPU. Generating data structures for random access is costly on the CPU, and the inefficiency increases dramatically when PCIe data transmission is incorporated. The third challenge is query processing on compressed data in GPU memory. Random accesses, including data updates, result in significant conflicts between massive threads. To solve the first challenge, we propose and modify a number of compressed data structures, including indexing within the complicated GPU memory hierarchy. To address the second challenge, we develop a two-phase process for generating these data structures on the GPU. To handle the third challenge, we propose a double-parsing design to avoid data conflicts. We evaluate our solution on two GPU platforms using five real-world datasets. Experiments show that the random access operations on GPU can achieve 65.04x average speedup compared to the state-of-the-art method.

关键词： Limiting Query processing Instruction sets High performance computing Memory management Graphics processing units data science

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Geometric Routing Precluding Loops and Dead Ends in 3-D Wireless Sensor Networks

Geometric Routing Precluding Loops and Dead Ends in 3-D Wire...

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2010 IEEE Global Telecommunications Conference GLOBECOM 2010

作者： Jun Duan Deying Li Wenping Chen Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China Beijing China

Numerous algorithms on geometric networks has been studied, and most of them were based on 2-dimensional networks. But 2-dimensional geometric routing algorithms cannot be directly adapted to the 3-dimensional networks. In this paper, we propose routing algorithms based on the iteration of specific angles on the networks of Delaunay Triangulation in 3D space, and prove the certainty of data transmission of our routing algorithms. In the algorithms, the messages only need to carry information of O(1) nodes and each node just keeps 1-hop neighbors' information.

关键词： Routing Peer to peer computing Three dimensional displays Algorithm design and analysis Compass Wireless sensor networks Relays

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Page Query Language Generation for Structural Extraction

Page Query Language Generation for Structural Extraction

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The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

作者： He Hu Xiaoyong Du School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge EngineeringMOE BeijingChina

ISBN: (纸本)9781479951499

The information on the Web is usually fabricated to be understandable by human users rather than ***'s not easy to automatically catalogue and extract the Web information solely with a software *** on these observations,we present an approach that uses human guided operations to automatically generate a PQL query,a SQL like query language focusing on Web pages,to extract the interested information fragments on Web *** PQL query uses XPath expressions to locating the target HTML *** develop a K-Medoid clustering algorithm to process PQL queries to generate the structural *** extracted information is structured as a relational table(in CSV format)which can be manipulated smoothly with spreadsheet software or a relational DBMS system.

关键词： PQL Structural Extraction Browser Extension

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In-Network Execution of External Join for Sensor Networks

In-Network Execution of External Join for Sensor Networks

引用

International Conference on Web-Age Information Management Workshops (WAIM)

作者： Yongxuan Lai Yilong Chen Hong Chen School of Information Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China

ISBN: (纸本)9781424432004;9780769531854

Recently there have been growing interests in the applications of wireless sensor networks such as traffic tracking, environmental surveillance, and network monitoring. In these applications, the exploration of the relationship and linkage of sensing data with other data sources can be naturally expressed by the external join, where the sensory tuples join with an external table at the base station. However, executing such kind of join queries in a highly distributed and resource-constraint sensor network is a challenging task. In this paper, we propose a partition-based algorithm called NEJA (in-network external join algorithm) for the external join processing in sensor networks. NEJA organizes the sensory data of the network through an optimized "value-to-storage" mapping, according to which each storage point stores the tuples that belong to the same subrange on the joint attribute. Then the subrange of each storage point is further partitioned into unit ranges, and tuples in the same unit range wisely choose their joining point that incurs the least communication cost based on a cost metric according to the latest historical statistics. Also, NEJA adopts some optimization techniques to handle the changes of sensory data and uses approximate approaches to cut down the maintenance cost of the mechanism. The experimental results indicate that our scheme is effective in reducing the amount of transmissions for the real time external join processing, especially when the external table has a relatively large size.

关键词： Base stations Joints Wireless sensor networks Sensors Partitioning algorithms Distributed databases Energy efficiency

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Computing Degree of Association Based on Different Semantic Relationships

Computing Degree of Association Based on Different Semantic ...

引用

International Workshop on database and Expert Systems Applications

作者： Xuan Tian Xiaoyong Du Haihua Li School of Information Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China

In domain ontologies, there is usually no weight assigned to the link between two concepts. This has been considered as one of main obstacles in using ontologies. Semantic Association (SA) is to depict the correlation of two concepts, and can be measured as the weight of the link. In this paper, we defined Degree of Association (DOA) to measure SA from a concept to its direct-related concept in domain ontology, and proposed a Language-Model-Based Method (LMBM) to compute DOA. Our idea comes from the intuition that the semantic relationship between two concepts implies certain semantic association of them. We took probabilistic model for computing DOA, and used Maximum Likelihood Estimation to estimate parameters. We tested the proposed method on two different domain ontologies, and applied it in experiments of semantic query expansion. Experimental results show the benefit of our approach and demonstrate the promising effectiveness over semantic query expansion.

关键词： Ontologies Information retrieval Direction of arrival estimation Parameter estimation data mining databases Expert systems Computer applications laboratories data engineering

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