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检索条件"机构=Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering"

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VSM-RF: A method of relevance feedback in keyword Search over Relational databases

VSM-RF: A method of relevance feedback in Keyword Search ove...

引用

IEEE International Symposium on Information (IT) in Medicine and education, ITME

作者： Zhao-hui Peng Jun Zhang Shan Wang Chang-liang Wang Li-zhen Cui School of Computer Science and Technology Shandong University Jinan 250101 China School of Computer Science and Technology Dalian Maritime University 116026 China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing 100872 China The Hong Kong University of Science and Technology China

In keyword search over relational databases (KSORD), retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. In this paper, a method of automatically reformulating user queries by relevance feedback is introduced, which is named VSM-RF. Aimed at the results of KSORD systems, VSM-RF adopts a ranking method based on vector space model to rank KSORD results. After the first time of retrieval, using user feedback or pseudo feedback just as user like, VSM-RF computes expansion terms based on probability and reformulates the new query using query expansion. After KSORD systems executing the new query, more relevant results are produced by the new query in the result list and presented to user. Experimental results verify this method's effectiveness.

关键词： Feedback keyword search Relational databases Computer science Information retrieval Laboratories data engineering knowledge engineering Computer science education Costs

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Bring User Feedback into keyword Search over databases

Bring User Feedback into Keyword Search over Databases

引用

Web Information Systems and Applications Conference (WISA)

作者： Zhaohui Peng Jun Zhang Shan Wang Changliang Wang School of Computer Science & Technology Shandong University Jinan China Key Laboratory of Data Engineering & Knowledge Engineering Ministry of Education Beijing China School of Computer Science & Technology Dalian Maritime University Dalian China Hong Kong University of Science and Technology Hong Kong China

keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. A method of automatically reformulating user queries by user feedback aimed at the results of KSORD is introduced in this paper, which is named UFBP (user feedback based on probability). After the first time of retrieval, according to the users' feedback information, UFBP computes terms to be added into the expanded query based on probability and reformulates the new query using query expansion. After KSORD executing the new query automatically, more relevant results are presented to user. Experimental results verify its effectiveness.

关键词： Feedback keyword search Relational databases Tree graphs Information retrieval Computer science educational technology Writing Information systems Application software

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A Novel Spatial Obstructed Distance Using Quantum-Behaved Particle Swarm Optimization

A Novel Spatial Obstructed Distance Using Quantum-Behaved Pa...

引用

International Conference on Intelligent Computation Technology and Automation, ICICTA

作者： Xueping Zhang Hong Yi Dan Cao Yawei Liu Tengfei Yang Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou China School of Information Science & Engineering Henan University of Technology Zhengzhou China

Spatial clustering with obstacles constraints (SCOC) has been a new topic in spatial data mining (SDM). Spatial obstructed distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel spatial obstructed distance using quantum-behaved particle swarm optimization (QPSO) based on grid model to obtain obstructed distance, which is named QPGSOD. The experimental results show that QPGSOD is effective, and it can not only give attention to higher local constringency speed and stronger global optimum search.

关键词： Particle swarm optimization Clustering algorithms Quantum computing data mining educational technology Automation Information science data engineering Laboratories Constraint optimization

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Modeling Email Worm Propagation Using Game Theory

Modeling Email Worm Propagation Using Game Theory

引用

The First International Conference on Multimedia Information Networking and Security(第一届国际多媒体网络信息安全会议 MINES 2009)

作者： Xin Sun Yanheng Liu Jian Wang College of Computer Science and Technology Jilin University Changchun Jilin 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin 130012 China

One of the most prevalent security problems in network is the rampant propagation of email worms. In this paper game theory is suggested as a method for modeling and computing the probabilities of expected behaviors of email users in the email worm propagation process. The game situation models the actions of the email users under the condition that at the time they open an attachment, the system may be infected. Results of email worm propagation simulation under a practical simulation environment show that well camouflaged worms spread more quickly and survive longer than naive worms, moreover, user's security consciousness and the update frequency of anti-virus software make great impact on email worm propagation.

关键词： Netwok security Game theory Email worm propagation User behavior

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Spatial Clustering with Obstacles Constraints by Ant Colony Optimization and Quantum Particle Swarm Optimization

Spatial Clustering with Obstacles Constraints by Ant Colony ...

引用

International Conference on Artificial Intelligence and Computational Intelligence (AICI)

作者： Xueping Zhang Jianjun Wu Haifang Si Tengfei Yang Yawei Liu Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou China School of Information Science & Engineering Henan University of Technology Zhengzhou China

The paper proposed a novel ant colony optimization (ACO) and quantum particle swarm optimization (QPSO) method for spatial clustering with obstacles constraints (SCOC). We first developed AQPGSOD using ACO and QPSO based on grid model to obtain obstructed distance, and then we presented a new QPKSCOC based on QPSO and K-Medoids to cluster spatial data with obstacles. The experimental results show that AQPGSOD is effective, and QPKSCOC can not only give attention to higher local constringency speed and stronger global optimum search, but also get down to the obstacles constraints and practicalities of spatial clustering.

关键词： Ant colony optimization Particle swarm optimization Quantum computing data mining Clustering algorithms Artificial intelligence Computational intelligence Information science data engineering educational technology

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A New Framework for Accessing Trusted Network

A New Framework for Accessing Trusted Network

引用

International Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Jian Wang Yanheng Liu Xiangpeng Jia Xiaomin Liu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN China Mobile Shenyang Branch Corporation Shenyang China

Trusted network connect (TNC), whose goal is to improve network security from source, now has become hot topic in security domain. We proposed a new access model for the terminals without meeting the requirements in TNC specifications. Also we discussed the work flow and communication process of presented model. Simulations show that the feasibility of the presented model used in the scenario where terminals fall short of network demand can pass the access authentication of network with TNC specifications.

关键词： Authentication Computer networks Protection Computer architecture Computer security Intelligent networks data security Intrusion detection Access control Peer to peer computing

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Extracting Attributes from Deep Web Interface Using Instances

Extracting Attributes from Deep Web Interface Using Instance...

引用

Computer Science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Hao Liang Fei Ren Wanli Zuo Fengling He Junhua Wang College of Computer Science and Technology Jilin University Changchun China Department of Information Changchun Taxation College Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China

There is myriad high quality information in the Deep Web and the feasible method to access the Deep Web is through the query interface of the Deep Web. Itpsilas necessary to extract abundant attributes and semantic relation description from the query interface. Automatic extracting attributes from the query interface and automatically translating a query is a solvable way for addressing the current limitations in accessing Deep Web data sources. We design a framework to automatically extract the attributes and instances from the query interface using the WordNet as a kind of ontology technique to enrich the semantic description of the attributes. Each attribute is extended into a candidate attribute set in the form of a hierarchy tree. At the same time, the hierarchy tree generated by ontology describes the semantic relation of the attributes in the same query interface. We carry out our experiments in the real-world domain. The results of the experiments showed the validation of query translation framework.

关键词： data mining Ontologies Computer science educational institutions databases Programming profession HTML Laboratories Computer interfaces knowledge engineering

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The Ontology Based Semantic Evaluating Method in LAV

The Ontology Based Semantic Evaluating Method in LAV

引用

Pacific-Asia Conference on Circuits, Communications and Systems, PACCS

作者： Fei Ren Hao Liang Liang Hu Wanli Zuo College of Computer Science and Technology Jilin University Changchun China Department of Information Changchun Taxation College Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

The Web has been dramatically deepened by the deep Web, which the traditional information fusion system shows disability to integrate. The myriad information hidden behind the deep Web attracts the considerable attention from the researchers. The key element in a deep Web information fusion system is the data source modeling problem, which determine the whole technical method of the whole system. The query interfaces provided by the deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the low generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of evaluating the semantic relationships between the attributes in the query interfaces by utilizing WordNet, a typical ontology technique, is presented in this paper. The semantic relationships between semantic related attributes are evaluated by the semantic calculating method of WordNet. The meaningless attributes is instantiated by instance information embedded in the interfaces in order to attach correlated semantic information. The experiment is carried out in the real life domains, and the result shows the efficiency of ontology based semantic evaluating method in LAV.

关键词： Ontologies databases educational institutions Computer science educational technology Search engines Circuits Laboratories knowledge engineering Computer science education

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Using IACO and QPSO to solve spatial clustering with obstacles constraints

Using IACO and QPSO to solve spatial clustering with obstacl...

引用

IEEE International Conference on Automation and Logistics

作者： Xueping Zhang Hongmei Zhang Yanxia Zhu Yawei Liu Tengfei Yang Taogai Zhang Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou China School of Computer Science & Engineering Henan University of Technology Zhengzhou Henan China Department of Computer Science & Engineering Henan University of Engineering Zhengzhou China

ISBN: (纸本)9781424447947

Spatial clustering has been an active research area in the data mining community. Spatial clustering is not only an important effective method but also a prelude of other task for spatial data mining (SDM). In this paper, we propose an improved ant colony optimization (IACO) and quantum particle swarm optimization (QPSO) method for spatial clustering with obstacles constraints (SCOC). In the process of doing so, we first use IACO to obtain the shortest obstructed distance, and then we develop a novel QPKSCOC based on QPSO and K-Medoids to cluster spatial data with obstacles. The experimental results demonstrate that the proposed method, performs better than Improved K-Medoids SCOC in terms of quantization error and has higher constringency speed than Genetic K-Medoids SCOC.

关键词： Ant colony optimization data mining Particle swarm optimization Computer science Quantization Genetics Clustering algorithms Automation Logistics data engineering

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ARRAY: A Non-application-Related, Secure, Wide-Area Disaster Recovery Storage System

ARRAY: A Non-application-Related, Secure, Wide-Area Disaster...

引用

International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Lingfang Zeng Dan Feng Bharadwaj Veeravalli Qingsong Wei Division of Data Storage System Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Electrical and Computer Engineering National University of Singapore Singapore Data Storage Institute Singapore

With our society more information-driven, we have begun to distribute data in wide-area storage systems. At the same time, both physical failure and logic error have made it difficult to bring the necessary recovery to bear on remote data disaster, and understanding this proceeding. We describe ARRAY, a system architecture for data disaster recovery that combines reliability, storage space, and security to improve performance for data recovery applications. The paper presents an exhaustive analysis of the design space of ARRAY systems, focusing on the trade-offs between reliability, storage space, security, and performance that ARRAY must make. We present RSRAII (Replication-based Snapshot Redundant Array of Independent Imagefiles) which is a configurable RAID-like data erasure-coding, and also others benefits come from consolidation both erasure-coding and replication strategies. A novel algorithm is proposed to improve snapshot performance referred to as SMPDP (Snapshot based on Multi-Parallel Degree Pipeline).

关键词： Secure storage Network servers Bandwidth Redundancy data security Cities and towns Laboratories educational technology Hardware History

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