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More efficient ontology matching algorithm for integrating heterogeneous web resources

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Journal of Southeast University(English Edition) 2007年第3期23卷 381-384页

作者：刘晨韩燕波陈旺虎丁维龙中国科学院计算技术研究所山东科技大学信息科学与技术学院青岛266510

To improve the performance of the ontology matching process, a more efficient ontology matching algorithm, which can effectively eliminate unnecessary operations of matching entities, is proposed. By the theoretical analysis and proof, a set of matching rules are summarized for depicting inherent relations among matching results of entities. Based on these rules, the proposed algorithm can reuse the matching results of two entities to directly determine the matching results of their adjacent entities. Thereby, redundant operations of matching adjacent entities can be avoided, which can improve the performance of the whole matching process. The experimental results show that, compared with related algorithms, the proposed algorithm has high matching accuracy and can remarkably reduce the consuming time of the whole matching process. So, the proposed algorithm is more competent for the large-scale ontology matching which often occurs in the practical heterogeneous web resources integration project.

关键词： ontology matching matching performance matching rule

An Improved Ant Colony Optimization for ontology matching

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An Improved Ant Colony Optimization for Ontology Matching

A matching Algorithm Based on Association Rules in ontology Based Publish/Subscribe System

2011 3rd International Conference on Computer Research and Development(ICCRD 2011)

作者： Xiaoyun Wang Qiyu Xu Institute of Management Science & Information Engineering Hangzhou Dianzi University Hangzhou China

The Hungarian algorithm used in ontology matching sometimes cannot get the solution since this algorithm does not converge when dealing with special *** order to solve this problem,this paper presents an improved ant colony optimization for ontology matching problem（ACOM）.We utilize many kinds of rating functions which are also called base matchers to evaluate the distance of two ontology *** getting the distance matrix of ontology entries,we use an improved ant colony optimization algorithm to extract the best alignment instead of using the traditional Hungarian ***,a set of experiments are conducted to analysis and evaluate the performance of ACOM in solving ontology matching *** use ontology Alignment Evaluation Initiative（OAEI） benchmark test suite with pairs of ontologies as test cases and compare our results with three algorithms presented in the OAEI *** results of experiments show that our system has a good performance in the ontology matching process.

关键词： semantic web ontology matching ant colony algorithm

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Chinese Journal of Electronics 2015年第1期24卷 65-70页

作者： LIU Shufen CHI Meng YAO Zhilin College of Computer Science and Technology Jilin University

In this paper, we introduce association rules into the event matching process, and propose a matching algorithm based on association rules in ontologybased publish/subscribe system. The algorithm discovers association rules from subscriptions, and then integrates these association rules into the arrived events. These integrated association rules guide the event matching process,which can greatly improve efficiency by reducing unnecessary matching processes. To solve the available problem of integrating the association rules into the ontology-based publish/subscribe system, we also show an approach of transforming the subscriptions into a format that can apply the data mining algorithm and an approach of integrating the association rule into the events. The results show that the algorithm achieves performance improvement of matching efficiency by using comparison.

关键词： Association rules ontology matching Publish/subscribe system.

Extracting Semantic Subgraphs to Capture the Real Meanings of ontology Elements

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Tsinghua Science and Technology 2010年第6期15卷 724-733页

作者：汪鹏徐宝文周毓明 School of Computer Science and Engineering Southeast University State Key Laboratory for Novel Software Technology Nanjing University Department of Computer Science and Technology Nanjing University

An element may have heterogeneous semantic interpretations in different ontologies. Therefore, understanding the real local meanings of elements is very useful for ontology operations such as querying and reasoning, which are the foundations for many applications including semantic searching, ontology matching, and linked data analysis. However, since different ontologies have different preferences to describe their elements, obtaining the semantic context of an element is an open problem. A semantic subgraph was proposed to capture the real meanings of ontology elements. To extract the semantic subgraphs, a hybrid ontology graph is used to represent the semantic relations between elements. An extracting algorithm based on an electrical circuit model is then used with new conductivity calculation rules to improve the quality of the semantic subgraphs. The evaluation results show that the semantic subgraphs properly capture the local meanings of elements. ontology matching based on semantic subgraphs also demonstrates that the semantic subgraph is a promising technique for ontology applications.

关键词： ontology ontology graph semantic subgraph ontology matching

GeoLink Data Set:A Complex Alignment Benchmark from Real-world ontology

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Data Intelligence 2020年第3期2卷 353-378页

作者： Lu Zhou Michelle Cheatham Adila Krisnadhi Pascal Hitzler DaSe Lab Kansas State UniversityManhattanKS 66506USA Wright State University DaytonOH 45435USA Faculty of Computer Science Universitas IndonesiaDepokJawa Barat 16424Indonesia

ontology alignment has been studied for over a decade,and over that time many alignment systems and methods have been developed by researchers in order to find simple 1-to-1 equivalence matches between two ***,very few alignment systems focus on finding complex *** reason for this limitation may be that there are no widely accepted alignment benchmarks that contain such complex *** this paper,we propose a real-world data set from the GeoLink project as a potential complex ontology alignment *** data set consists of two ontologies,the GeoLink Base ontology(GBO)and the GeoLink Modular ontology(GMO),as well as a manually created reference alignment that was developed in consultation with domain experts from different *** alignment includes 1:1,1:n,and m:n equivalence and subsumption correspondences,and is available in both Expressive and Declarative ontology Alignment Language(EDOAL)and rule *** benchmark has been expanded from its original version to contain real-world instance data from seven geoscience data providers that has been published according to both *** allows it to be used by extensional alignment systems or those that require training *** benchmark has been incorporated into the ontology Alignment Evaluation Initiative(OAEI)complex track to help researchers test their automated alignment systems and *** paper also analyzes the challenges inherent in effectively generating,detecting,and evaluating complex ontology alignments and provides a road map for future work on this topic.

关键词： ontology matching Complex ontology alignment Real-world ontology ontology population Complex ontology alignment benchmark

Application of Improved Compact Particle Swarm Optimization to Large ontology Alignment Task

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Wuhan University Journal of Natural Sciences 2021年第4期26卷 339-348页

作者： LV Zhaoming PENG Rong School of Computer Science Wuhan UniversityWuhan 430072HubeiChina

ontology occupies an important position in artificial intelligence,computer linguistics and knowledge ***,when different ontologies are constructed to represent the same information in a domain,the so-called heterogeneity problem *** order to address this problem,a key task is to discover the semantic relationship of entities between given two ontologies,called ontology ***,the meta-heuristic algorithms have already been regarded as an effective approach for solving ontology alignment ***,firstly,as the ontologies become increasingly large,meta-heuristic algorithms may be easier to find local optimal alignment in large search ***,many existing approaches exploit the population-based meta-heuristic algorithms so that the massive calculation is *** this paper,an improved compact particle swarm algorithm by using a local search strategy is proposed,called LSCPSOA,to improve the performance of finding more correct *** LSCPSOA,two update strategies with local search capability are employed to avoid falling into a local optimal *** proposed algorithm has been evaluated on several large ontology data sets and compared with existing ontology alignment *** experimental results show that the proposed algorithm can find more correct correspondences and improves the time performance compared with other meta-heuristic algorithms.

关键词： ontology matching compact particle swarm optimization multiple updating strategies

VDoc+:a virtual document based approach for matching large ontologies using MapReduce

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Journal of Zhejiang University-Science C(Computers and Electronics) 2012年第4期13卷 257-267页

作者： Hang ZHANG Wei HU Yu-zhong QU State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Nanjing UniversityNanjing 210093China

Many ontologies have been published on the Semantic Web,to be shared to describe *** them,large ontologies of real-world areas have the scalability problem in presenting semantic technologies such as ontology matching(OM).This either suffers from too long run time or has strong hypotheses on the running *** deal with this issue,we propose a three-stage MapReduce-based approach V-Doc+ for matching large ontologies,based on the MapReduce framework and virtual document ***,two MapReduce processes are performed in the first stage to extract the textual descriptions of named entities(classes,properties,and instances) and blank nodes,*** the second stage,the extracted descriptions are exchanged with neighbors in Resource Description Framework(RDF) graphs to construct virtual *** extraction process also benefits from the MapReduce-based implementation.A word-weight-based partitioning method is proposed in the third stage to conduct parallel similarity calculation using the term frequency-inverse document frequency(TF-IDF) *** results on two large-scale real datasets and the benchmark testbed from ontology Alignment Evaluation Initiative(OAEI) are reported,showing that the proposed approach significantly reduces the run time with minor loss in precision and recall.

关键词： ontology matching Virtual document MapReduce TF-IDF Semantic Web