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Ontology-assisted schema matching for deep web query interfaces

Journal of Information and computational Science 2010年第2期7卷 543-549页

作者： Wang, Ying Zuo, Wanli Wang, Xin Zhang, Aiqi Peng, Tao College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Computation and Knowledge Engineering Ministry of Education China College of Software Changchun Institute of Technology Changchun 130012 China

Schema matching is important for schema integration and thus has got great attention. In this paper, we present an ontology-based algorithm to match a larger number of interface schemas, which can hand both simple and complex mappings of attributes. Firstly, construct a core ontology and the semantics of concepts in the core ontology can be enriched during schema matching. Secondly, design the ontology-assisted schema matching algorithmic for deep web query interface. Lastly, capture the matching relationships between source schema and target schema using domain-specific ontology. During the schema matching of deep web entries, ontology is the ″bridging″ which is used to obtain the mapping relationships between different query interfaces. Experiment result shows that this method is feasible and effective. Copyright © 2010 Binary Information Press.

关键词： Ontology

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Using SROIQB to model and compose semantic Web service

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Tongxin Xuebao/Journal on Communications 2010年第8 A期31卷 1-9页

作者： Liu, Da-You Liu, Si-Pei Qi, Hong College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

One kind of semantic Web service modeling and reasoning method based on description logic with Boolean role constructors (SROIQB) was introduced. By using DL to figure out the hyponymy relationship between concepts in domain ontology and model Web service functional semantic in ServiceProfile, and define Boolean role expressions to describe the composition process in ProcessProfile respectively. Furthermore, Boolean role expression is introduced to describe all possible composition structures of atomic services and then semantic Web service composition can be regarded as a process of consistence checking and class subsumption computing reasoning on DL knowledge base. Thus the comparison and example validation show that introduced one kind of new and reasonable semantic Web service modeling and composition method in the framework of semantic Web by using SROIQB, which with more strong expressive capability and decidable type inference.

关键词： Semantic Web

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Describing the semantic relation of the deep web query interfaces using ontology extended LAV

Journal of Software

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Journal of Software 2010年第1期5卷 89-98页

作者： Liang, Hao Zuo, Wan-Li Ren, Fei Department of Computer Science and Technology Jilin University Jilin Changchun China Department of Information Changchun Taxation College Jilin Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor 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 lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema. © 2010 ACADEMY PUBLISHER.

关键词： Ontology

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Mining data records based on ontology evolution for deep web

Mining data records based on ontology evolution for deep web

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International Conference on Computer engineering and Technology, ICCET

作者： Wen Zhang Kerui Chen Fan Zhang College of Information Engineering Zhongzhou University Zhengzhou China College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Currently, the research for the extraction of information in deep web is pretty active. Although many researchers already adopted ontology in the data extraction, many problems still exist. This paper proposed an ontology evolution based method for mining in the data area. Not only will this method solve the problem when the website only consists of one record, but it also can identify he meaning of data that has no labels. With the evolution of ontology, the extraction of data records is being more accurate. Experiments indicate that this method could improve the accuracy and efficiency of data extraction.

关键词： Data mining Ontologies Entropy Educational institutions knowledge engineering Web pages Data engineering Random processes Computer science Educational technology

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Heterogeneous deep web data extraction using ontology evolution

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Journal of Convergence Information Technology 2010年第8期5卷 23-23页

作者： Chen, Kerui Zhao, Jinchao Zuo, Wanli He, Fengling Chen, Yongheng College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China

This paper proposed a complex ontology evolution based method of extracting data, and also completely designed an extraction system, which consists of four important components: Resolver, Extractor, Consolidator and the ontology construction components. The system gives priority to the construction of mini-ontology. When the user submits query keywords to the deep web query interface, the returned result will pass through the prior three components;after that, the final execution result will be returned to user in a unified form. This paper adopted an extraction method that is different from the general ontology extraction. More specifically, the ontology used in extraction here is dynamic evolution, which can adapt various data source better. Experimental results proved that this method could effectively extract the data in the query result pages.

关键词： Ontology

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A NEW CASCADING FAILURE MODEL WITH DELAY TIME IN CONGESTED COMPLEX NETWORKS

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Journal of Systems Science and Systems engineering 2009年第3期18卷 369-381页

作者： Jian WANG Yanheng LIU Yu JIAO College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process： generation, diffusion, and dissipation of congestion. Different from the betweenness centrality, a congestion function is proposed to represent the extent of congestion on a given node. Inspired by the restart process of a node, we introduce the concept of ＂delay time,＂ during which the overloaded node Cannot receive or forward any traffic, so an intergradation between permanent removal and nonremoval is built and the flexibility of the presented model is demonstrated. Considering the connectivity of a network before and after cascading failures is not cracked because the overloaded node are not removed from network permanently in our model, a new evaluation function of network efficiency is also proposed to measure the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability, and traffic generation speed on congestion propagation. Cascading processes composed of three phases and some factors affecting cascade propagation are uncovered as well.

关键词： Complex networks cascading failures congestion effects propagation model

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Genetic algorithm with affinity propagation

Genetic algorithm with affinity propagation

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International Conference on Information and Automation (ICIA)

作者： Chunguo Wu Hao Gao Lianjiang Yu Yanchun Liang Rongwu Xiang College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry Jilin University Changchun China School of Basic Courses Shenyang Pharmaceutical University Shenyang China

ISBN: (纸本)9781424457014

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems, e.g., aerodynamic design optimization, qualitative model learning in bioinformatics. To address this problem, we present a combination between genetic algorithms and clustering methods. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.

关键词： Genetic algorithms Clustering methods Evolutionary computation Design optimization Optimization methods Design automation Computer science Educational technology Pharmaceutical technology knowledge engineering

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A hybrid algorithm of minimum spanning tree and nearest neighbor for classifying human cancers

A hybrid algorithm of minimum spanning tree and nearest neig...

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International Conference on Advanced Computer Theory and engineering, ICACTE

作者： Chunbao Zhou Liming Wan Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China Research Institute on General Development and Evaluation of Equipment EAAF of PLA Beijing China

ISBN: (纸本)9781424465392

Classification and prediction of different cancers based on gene expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. The k nearest neighbor algorithm (k-NN) is one easy and efficient machine learning method for cancer classification and the parameter k is crucial. In this paper, we integrate minimum spanning tree (MST) and k nearest neighbor algorithm (k-NN) for cancer classification. The MST is designed for the selection of parameter k and the nearest neighbors for k-NN. Firstly we build a minimum spanning tree (MST) based on Euclidean distance between each two samples for gene expression data only including one unknown class sample. Secondly for unknown class sample in the gene expression data, we find the connected samples and then apply majority vote principle. Thirdly if there are tied votes then we expend the connected samples with the nearest neighbors for unknown class sample until all the samples are expended or the class for unknown sample is obtained. This hybrid algorithm is referred to as MSTNN. The hybrid algorithm MSTNN is compared with k-NN and other 3 existing classification algorithms on CNS dataset, Colon dataset and Lung dataset, 3 binary class gene expression datasets and 3 multi-class gene expression datasets: Leukemia1, Leukemia2, and Leukemia3 involving human cancers. The MSTNN algorithm improves 5.65% better than k-NN on average LOOCV accuracy and 13.80% better than k-NN on testing datasets classification average accuracy, and achieves the best performance in all the 5 algorithms. The results demonstrate that the proposed MSTNN algorithm is feasible to classify human cancers.

关键词： Classification algorithms Artificial neural networks Niobium Lungs Colon Support vector machines Cancer

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Deriving all minimal consistency-based diagnosis sets using SAT solvers

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Progress in Natural Science:Materials International 2009年第4期19卷 489-494页

作者： Xiangfu Zhao a,b, Liming Zhang a,b, Dantong Ouyang a,b, Yu Jiao a,b a key laboratory of symbolic computation and knowledge engineering of Ministry of Education, Jilin University, Changchun 130012, China b School of Computer Science and Technology, Jilin University, Changchun 130012, China [a]Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China [b]School of Computer Science and Technology Jilin University Changchun 130012 China

In this paper, a novel method is proposed for judging whether a component set is a consistency-based diagnostic set, using SAT solv- ers. Firstly, the model of the system to be diagnosed and all the observations are described with conjunctive normal forms (CNF). Then, all the related clauses in the CNF files to the components other than the considered ones are extracted, to be used for satisfiability checking by SAT solvers. Next, all the minimal consistency-based diagnostic sets are derived by the CSSE-tree or by other similar algorithms. We have implemented four related algorithms, by calling the gold medal SAT solver in SAT07 competition – RSAT. Experimental results show that all the minimal consistency-based diagnostic sets can be quickly computed. Especially our CSSE-tree has the best effciency for the singleor double-fault diagnosis.

关键词： Conjunctive normal form Consistency-based diagnosis Model-based diagnosis SAT solver

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Computing minimal diagnosis with binary decision diagrams algorithm

Computing minimal diagnosis with binary decision diagrams al...

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6th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2009

作者： Wang, Kun Li, Zhan-Shan Ai, Yang Zhang, Yong-Gang Key Laboratory of Symbolic Computation Knowledge Engineering for Ministry of Education Jilin University Jilin Changchun China

ISBN: (纸本)9780769537351

In this paper we propose an algorithm of computing minimal diagnosis based on BDD (Binary Decision Diagram). First we give the concept of disjunction equations, and map the collection of conflict sets into disjunction equations, then we compile the system into a BDD, further we compute the minimal hitting sets by solving the BDD and minimizing hitting sets. The reliability and completeness of the algorithm are proved. Variable ordering and construct controlling of BDD are used to further reduce the size of final BDD and the number of non-minimal hitting sets to be generated. The efficiency of computing minimal hitting sets is highly improved. Experimental results show that the algorithm isn't restricted by the structure of system and conflict sets, compared with three algorithms in the references, it can generate all the minimal hitting sets, and it works well in random circumstances. © 2009 IEEE.

关键词： Binary decision diagrams

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