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Research on Web Services Selection Model Based on AHP

Research on Web Services Selection Model Based on AHP

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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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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OLTP workloads on modern processor: Characterization and analysis

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Journal of Computational Information Systems 2008年第1期4卷 389-394页

作者： Liu, Dawei Qin, Biao Wang, Shan Gong, Weiwei School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 200872 China

This paper analysis of how OLTP workloads interact with modern processors and caches behavior. First, we extend TPC-C, the OLTP-oriented benchmark, to ETPC-C benchmark, for measuring the performance of main-memory database (MMDBMS) more precisely. As the performance of MMDBMS is not affected by disk I/O, it is more sensitive to cache usage. Then using ETPC-C benchmark, we investigated the behavior of caches and processors extensively. We find that the miss stall time is mostly spent on on-CPU-chip caches, that is, the first and second level cache misses are dominant. Furthermore, we find instruction cache (I-cache) stall time of on-CPU-chip is a major component to the memory stall time. The smaller the emulated users, the more proportion the I-cache stall time of on-CPU-chip contributes to the memory stall time. However, if employing index, the system under test (SUT) has more total I-cache stall time than the SUT without index at the same number of emulated users and data population. Another observation is that the SUT with index has a little more branch misprediction rate than the SUT without index in average. Finally, we find only the third level (L3) D-cache stall time rate increases with the number of users. This is because L3 D-cache miss incremental rate is the largest. Under TPC-and ETPC-evaluation, we find that for optimized database performance on modern computers, reducing instruction miss penalty is equally important to reducing data miss penalty;since they are conflict efforts, the best way is to have them balanced.

关键词： Program processors

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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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Shingles-based structural clustering of web documents

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Journal of Computational Information Systems 2008年第6期4卷 2777-2785页

作者： Xia, Tian Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China School of Information Resource Management Renmin University of China Beijing 100872 China

Web document structural clustering is a useful task for many web intelligent applications, however, processing based on the structure of web documents have not yet received strong attention. In this paper, we propose a shingles-based approach to clustering web documents by structure. Firstly, semi-structured web documents are converted into structured tree which composed of a set of limited nodes, and structural features are extracted by shingles. Secondly, we define document distance and structural distance matrix, and then structural similarity is calculated according to this matrix. Finally, we cluster the document structure based on modified k-means algorithm. Different from existing methods, we construct shingles not only including real vertical paths, but also virtual horizontal paths. Weight factors are also considered to optimize the algorithm. Experimental results show the effectiveness of the new shingles-based similarity measurement and the structural clustering. The proposed document similarity, as well as the structural shingles analysis, could be applied to other web-based research issues. © 2008 Binary Information Press.

关键词： Information systems

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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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The Design of an Open Hybrid Recommendation System for Mobile Commerce

The Design of an Open Hybrid Recommendation System for Mobil...

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce

作者： Chengzhi Liu Caihong Sun Jia Yu Information School and Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia

To meet more and more complex recommendation needs, it is quite important to implement hybrid recommendations for mobile commerce. In this paper, we propose a design for open hybrid recommendation systems in mobile commerce, which could integrate multiple recommendation algorithms together to improve recommendation performance. First, three solutions for an open hybrid recommendation approach are discussed in detail, which are generic customer profile, weighted hybrid recommendation algorithm, and mobile device profile creation. After that, we give out a multi-agent architecture design to make the three solutions work together. Finally a prototype system based on our proposed architecture is implemented to demonstrate the feasibility of our design and evaluate the performance of the proposed open hybrid recommendation system.

关键词： Business Customer profiles Context awareness Laboratories data engineering knowledge engineering Prototypes XML Sun Australia

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Energy Efficient Multicast Routing for Discrete Power Levels in Ad Hoc Sensor Networks

Energy Efficient Multicast Routing for Discrete Power Levels...

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The 4th International Conference on Wireless Communications, Networking and Mobile Computing(第四届IEEE无线通信、网络技术及移动计算国际会议)

作者： Deying Li Qinghua Zhu Zheng Li Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE Scho School of Information Renmin University of China Beijing 100872 P.R.China

In this paper, we discuss the energy efficient multicast problem for discrete power levels in ad hoc sensor wireless networks. The problem of our concern is: given n nodes and each node v has l(v) transmission power levels and a multicast request (s, D), how to find a multicast tree rooted at s and spanning all destinations in D such that the total energy cost of the multicast tree is minimized. This problem is NP-hard. We propose a NWM_DST algorithm which has a theoretical guaranteed approximation performance ratio, and two efficient heuristics MNJT and g-D-MIP for multicast tree problem. Simulation results have shown efficiency of our proposed algorithms.

关键词： wireless sensor network energy efficiency approzimation algorithm multicast routing

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