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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2008年 4977卷 134-143页

作者： Li, Peng Zhu, Qing Wang, Shan Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing100872 China

ISBN: (纸本)354089375X

With the development of relational database, people require better database not only in the aspect of database performance, but also in the aspect of the database’s interactive ability. So that the database is much more friendly than just before and it is possible for a common user who do not have any special knowledge on database can access the database, without knowing the schema of database and writing intricate SQL. For the reason that the information retrieval on the web has developed well to some extent, when we develop the technology of keyword search in relational database, we can draw some ideas from information retrieve. But the great differences between the text database on the web and the relational database also bring some new challenges: 1) The answer needed by user is not only one tuple in database, but the tuple sets consisting of the tuple connect from different table using the "primary key-foreign key" relationship. 2)The results of the evaluation criteria is more important, because it is directly related to the effectiveness of Search System. 3)The structure of relational database is much more intricate than text database, and the algorithms of information retrieval are not fit the relational database. So in this paper, we introduce a novel keyword search algorithm and a modified criteria of evaluating answers in order to enhance efficiency of the keyword search and return much more effective information to users, finally, the search algorithm’s performance is tested and evaluated. © Springer-Verlag Berlin Heidelberg 2008

关键词： Information retrieval

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Power conservation for strongly connected topology control in wireless sensor network

Power conservation for strongly connected topology control i...

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1st ACM International Workshop on Foundations of Wireless Ad Hoc and Sensor Networking and Computing 2008, FOWANC'08

作者： Li, Deying Du, Hongwei Chen, Wenping School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Beijing 100872 China Department of Computer Science City University of Hong Kong Kowloon Hong Kong School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9781605581491

Topology control is one of the most elementary topics in wireless sensor networks. Typically, most of the research only considered the bidirectional communication and symmetric weighted communication model, while the real wireless world contains not only bidirectional but also unidirectional communication links and asymmetric weighted communication model. In this paper, we present two heuristics for the minimum power topology control problem on general model, i.e., given a set of sensors in the Euclidean plane and a transmission power threshold for each directed pair of sensors, to find a power assignment for each sensor to achieve a strong connectivity with minimum total transmission power. Extensive results in simulation evaluate the efficiency of the proposed algorithms. Copyright 2008 ACM.

关键词： Wireless sensor networks

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Greedy-Algorithm of KSORD Supporting Multi-language Phrase Recognition

Greedy-Algorithm of KSORD Supporting Multi-language Phrase R...

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International Conference on Advanced Computer Theory and engineering, ICACTE

作者： Peng Li Qing Zhu Chao Tian Shan Wang Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing China

With the rapid development of information retrieval technology and daily increasing information in the Internet, common users can retrieve many text-based database and get part of the information through the search engines such as Google, and Baidu. However, there is a great amount of data contained in the background relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison between our algorithm and the existing ones. The experiment results shows that our algorithm owns not only the feature of effectiveness but also the feature of efficiency.

关键词： Relational databases Internet Information retrieval data engineering knowledge engineering Search engines Dictionaries data structures Chaos Laboratories

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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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Mining Approximate Closed Frequent Itemsets over Stream

Mining Approximate Closed Frequent Itemsets over Stream

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

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

ISBN: (纸本)9780769532636

Frequent itemset mining is a very important problem in data mining. Closed frequent itemsets is the condensed representation of frequent itemsets thus spend less memory, so it is much suitable for stream mining. But on the other hand, when the minimum support is much lower, the size of closed frequent itemsets turns larger, which makes the performance reduced a lot. In this paper, we introduce a threshold to approximately mine closed frequent itemsets with a limited error tolerance. A new algorithm named ACFIM is proposed based on the introduction of the distance conception to mine the sliding window of stream, in which more data are pruned and more computation time are saved, so it much raise the performance in running time and memory comparing to the state-of-art closed frequent itemsets mining methods. Our experimental results over real-life datasets show that ACFIM is effective and efficient.

关键词： Itemsets data mining Distance measurement Pediatrics Approximation algorithms Approximation methods databases

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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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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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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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Using Ontology to Enhance Collaborative Recommendation Based on Community

Using Ontology to Enhance Collaborative Recommendation Based...

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

作者： Li Yu School of Information Key Laboratory of Data Engineering and Knowledge Engineerin Renmin University of China Beijing China

ISBN: (纸本)9781424432004;9780769531854

Collaborative filtering is an important personalized recommendation technique applied widely in E-commerce. It is not adapted to multi-interest or title recommendation for the 'general neighbourhood' problem which is analyzed in this paper. Based on it, collaborative filtering recommendation based on community is presented by introducing the concept 'community neighbourhood' in the paper. Unfortunately, it results into severer sparsity problem which makes heavy effect on its performance. In order to overcome it, an ontological A-priori score is used to infer user preference and to pre-fill null rating first. After pre-filling using the ontology method, then collaborative filtering based on community is executed based on a dense rating matrix. The experiment shows that collaborative filtering based on community makes generally better performance than traditional method when data is not very sparse, and ontology method can truly enhance collaborative filtering based on community since the sparsity is overcame.

关键词： Communities Ontologies Filtering Collaboration Motion pictures Filling Argon

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