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A Parallel Recovery Scheme for Update Intensive Main Memory database Systems

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

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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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Evolving Sequential Patterns Mining Model over Click Stream with Levenshtein-Automata

Evolving Sequential Patterns Mining Model over Click Stream ...

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International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Haifeng Li Hong Chen School of Information Key Laboratory of Data Engineering and Knowledge Engineering MOEMOE Renmin University of China Beijing China

Sequential pattern mining is an important problem in continuous, fast, dynamic and unlimited stream mining. Recently approximate mining algorithms are proposed which spend too many system resources and can only obtain the partial feature of stream. In this paper, a multi-level evolving sequential pattern mining model ESPMM is presented to address this problem thus the mostly entire stream feature is obtained. Furthermore, because of the smaller support of sequential patterns in each level, a mining method BMLA based on Levenshtein-Automata is proposed which builds state conversion model to compute sequences' similarity in linear time. The experiment results show this model is effective and efficient.

关键词： Distance measurement data mining Runtime Automata Computational modeling Evolution (biology) data models

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In-Network Execution of External Join for Sensor Networks

In-Network Execution of External Join for Sensor Networks

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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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Research on Web Services Selection Model Based on AHP

Research on Web Services Selection Model Based on AHP

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2008 IEEE International Conference on Service Operations and Logistics, and Informatics(IEEE/SOLI’2008)(IEEE服务运作、物流与信息年会)

作者： Bei Wu Meiyun Zuo Shijuan Wang Information School and Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China BeijingChina

This paper focuses on the problem that how to select the optimal service among many Web services which all meet the functional needs,establishes an index system for Web services products selection from four aspects,namely the supply side,the user,product and *** on this,we collect the views of 30 experts by Analytic Hierarchy Process (AHP) method and calculate the weight of each index at all levels based on the data collected from questionnaire *** the overall sample data analysis,we put two types of sample data namely business operation experts and academics for comparative *** Web services selection model proposed in this article can provide the reference to Web services managers when they selecting Web services,and also contributes to in-depth research on the adoption of Web services based information system.

关键词： web services selection model analytic hierarchy process information system

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Improve Frequent Closed Itemsets Mining over data Stream with Bitmap

Improve Frequent Closed Itemsets Mining over Data Stream wit...

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

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

ISBN: (纸本)9780769532639

Frequent itemsets mining is an important problem in data mining. Frequent closed itemsets mining provides complete and condensed information for frequent pattern analysis thus reduces the memory cost without accuracy loss. More research focus on stream mining with the more application of stream. Stream is fast and unlimited thus data had to be stored in limited memory, how to save running time and memory usage is the most important target. In this paper, we propose an improved frequent closed itemsets mining method based on traditional stream mining algorithm CFI-stream with bitmap coding named CLIMB (closed itemset mining with bitmap) over stream's sliding window. The distinct items are maintained in memory in lexicographic order and each itemset is coded to bit-sequence with the order of items, moreover, the bit-sequence is split into sections to be recoded to reduce the memory cost. The experimental results on real-life show that CLIMB algorithm is effective and efficient.

关键词： Itemsets data mining Encoding Decoding data structures Runtime Algorithm design and analysis

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Influence of Product's Characters on Supply Chain Coordination

Influence of Product's Characters on Supply Chain Coordinati...

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2008 IEEE International Conference on Service Operations and Logistics, and Informatics(IEEE/SOLI’2008)(IEEE服务运作、物流与信息年会)

作者： Li Qian Information School and Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of ChinaBeijing 100872China

In the research field of supply chain coordination,many coordination contracts have been well *** chain members still feel confused about which contract should be chosen for their specific needs and *** paper starts from the essential analysis of supply chain coordination,and summaries four important affecting factors as well as the attributes in coordination,including market demand,competitors' relationship,supply chain structure,and decisions *** importantly this paper studies the related products' characters,such as storage life,customer's loyalty,etc,which are seldom discussed in coordination before,and analyzes the influence in *** on these research,the chain members could analyze their specific product's characters and affecting factors,then choose the proper coordination contracts.

关键词： coordination contract market demand,competitors' relationship supply chain structure product’s influencing character

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CRO: A system for online review structurization

CRO: A system for online review structurization

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14th ACM SIGKDD International Conference on knowledge Discovery and data Mining, KDD 2008

作者： Liu, Hongyan Yang, Hui Li, Wenbo Wei, Wei He, Jun Du, Xiaoyong School of Economics and Management Tsinghua University Beijing 100084 China Information School Renmin University of China Beijing 100872 China School of Computer Science and Engineering Beihang University Beijing 100083 China Key Labs. of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing 100872 China

ISBN: (纸本)9781605581934

In this paper, we present a system called CRO (Chinese Review Observer) for online product review structurization. By Structurization, we mean identifying, extracting and summarizing information from unstructured review text to a structured table. The core tasks include review collection, product feature and user opinion extraction, and polarity analysis of opinions. Existing research in this area is mainly English text oriented. To deal with Chinese effectively, we propose several novel approaches for fulfilling the core tasks. Then we integrated these approaches and implement the whole procedure of review structurization in the system CRO. Running results for reviews of real products show its performance is satisfactory.

关键词： Sentiment analysis

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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 ...

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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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A New Dynamic Hash Index for Flash-Based Storage

A New Dynamic Hash Index for Flash-Based Storage

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

作者： Xiang Li Zhou Da Xiaofeng Meng Renmin University of China Beijing CN Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China China

Compared with traditional magnetic disks, flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, digital camera and mobile phone). As the capacity increases and price drops, it looks like a perfect alternative for magnetic disks. However, due to hardware limitations of flash memory, techniques including storage subsystem and indexing originally designed for magnetic disks can not run smoothly in a flash memory without any modification. In this paper we explore problems of indexing flash-resided data and present a new dynamical hash index for flash memory in two schemas. The analysis and experimental results validate the efficiency of our design.

关键词： Indexes Flash memory Algorithm design and analysis Writing Tuning Indexing Arrays

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Extracting Feature and Opinion Words Effectively from Chinese Product Reviews

Extracting Feature and Opinion Words Effectively from Chines...

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International Conference on Fuzzy Systems and knowledge Discovery (FSKD)

作者： Wei Wei Hongyan Liu Jun He Hui Yang Xiaoyong Du Information School Renmin University of China China School of Economics and Management Tsinghua University China Key Laboratory of Data Engineering and Knowledge Engineering MOE China

Nowadays more and more people like to publish their comments on a product on the Web. Mining such unstructured data (product reviews) is exciting hot and challenging research and application topic. In this paper, we focus on mining product reviews written in Chinese. We aim at extract the structural information from Chinese product reviews. By structural information, we mean product features and corresponding opinion words expressed in each review text. There are already some works done for reviews written in English, but less in Chinese. In this paper, we propose an effective method to extract candidate features and some effective pruning rules to prune the features. Also, we introduce a pattern extraction and matching step to improve our results. The experiment results show our approach is very effective, and has a good recall and precision.

关键词： Feature extraction data mining Negative feedback Information retrieval Fuzzy systems Conference management knowledge management engineering management Helium laboratories

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