An association rules mining method based on semantic relativity is proposed to solve the problem that there are more candidate item sets and higher time complexity in traditional association rules mining.Semantic rela...An association rules mining method based on semantic relativity is proposed to solve the problem that there are more candidate item sets and higher time complexity in traditional association rules mining.Semantic relativity of ontology concepts is used to describe complicated relationships of domains in the method.Candidate item sets with less semantic relativity are filtered to reduce the number of candidate item sets in association rules mining.An ontology hierarchy relationship is regarded as a directed acyclic graph rather than a hierarchy tree in the semantic relativity computation.Not only direct hierarchy relationships,but also non-direct hierarchy relationships and other typical semantic relationships are taken into account.Experimental results show that the proposed method can reduce the number of candidate item sets effectively and improve the efficiency of association rules mining.展开更多
To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain par...To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.展开更多
To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance...To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.展开更多
Semantic Web Services is an emerging technology that promises to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Semantic matchmaking plays a vital role in the automated and dyna...Semantic Web Services is an emerging technology that promises to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Semantic matchmaking plays a vital role in the automated and dynamic discovery process of Semantic Web Services and consists in measuring the semantic distance between a requested service and an advertised one. In this paper, an innovative approach to effectively compute the semantic distance between Ontology Web Language for Services （OWL-S） annotated services is proposed. First, an edge-based method for measuring the semantic distance between Web Ontology Language （OWL） concepts is presented. Then, a comparison of the proposed measure and the one presented in a recent related work is made in order to show that our method is more efficient and fine-grained. Finally, some equations to compute semantic matchmaking of service capabilities, which are expressed in terms of inputs and outputs, are presented.展开更多
A Kullback-Leibler（KL）distance based algorithm is presented to find the matches between concepts from different ontologies. First, each concept is represented as a specific probability distribution which is estimate...A Kullback-Leibler（KL）distance based algorithm is presented to find the matches between concepts from different ontologies. First, each concept is represented as a specific probability distribution which is estimated from its own instances. Then, the similarity of two concepts from different ontologies is measured by the KL distance between the corresponding distributions. Finally, the concept-mapping relationship between different ontologies is obtained. Compared with other traditional instance-based algorithms, the computing complexity of the proposed algorithm is largely reduced. Moreover, because it proposes different estimation and smoothing methods of the concept distribution for different data types, it is suitable for various concepts mapping with different data types. The experimental results on real-world ontology mapping illustrate the effectiveness of the proposed algorithm.展开更多
基金The National Natural Science Foundation of China(No.50674086)Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508)the Science and Technology Fund of China University of Mining and Technology(No.2007B016)
文摘An association rules mining method based on semantic relativity is proposed to solve the problem that there are more candidate item sets and higher time complexity in traditional association rules mining.Semantic relativity of ontology concepts is used to describe complicated relationships of domains in the method.Candidate item sets with less semantic relativity are filtered to reduce the number of candidate item sets in association rules mining.An ontology hierarchy relationship is regarded as a directed acyclic graph rather than a hierarchy tree in the semantic relativity computation.Not only direct hierarchy relationships,but also non-direct hierarchy relationships and other typical semantic relationships are taken into account.Experimental results show that the proposed method can reduce the number of candidate item sets effectively and improve the efficiency of association rules mining.
基金The National Basic Research Program of China(973 Program)(No.2010CB328104,2009CB320501)the National Natural Science Foundation of China(No.61070161,61070158,61003257, 61003311)+2 种基金the National Key Technology R&D Program during the 11th Five-Year Plan Period(No.2010BAI88B03)the Foundation of Jiangsu Provincial Key Laboratory of Netw ork and Information Security (No.BM2003201)Open Research Fund from Key Laboratory of Computer Netw ork and Information Integration of Ministry of Education (Southeast University)
文摘To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.
文摘To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.
文摘Semantic Web Services is an emerging technology that promises to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Semantic matchmaking plays a vital role in the automated and dynamic discovery process of Semantic Web Services and consists in measuring the semantic distance between a requested service and an advertised one. In this paper, an innovative approach to effectively compute the semantic distance between Ontology Web Language for Services （OWL-S） annotated services is proposed. First, an edge-based method for measuring the semantic distance between Web Ontology Language （OWL） concepts is presented. Then, a comparison of the proposed measure and the one presented in a recent related work is made in order to show that our method is more efficient and fine-grained. Finally, some equations to compute semantic matchmaking of service capabilities, which are expressed in terms of inputs and outputs, are presented.
文摘A Kullback-Leibler（KL）distance based algorithm is presented to find the matches between concepts from different ontologies. First, each concept is represented as a specific probability distribution which is estimated from its own instances. Then, the similarity of two concepts from different ontologies is measured by the KL distance between the corresponding distributions. Finally, the concept-mapping relationship between different ontologies is obtained. Compared with other traditional instance-based algorithms, the computing complexity of the proposed algorithm is largely reduced. Moreover, because it proposes different estimation and smoothing methods of the concept distribution for different data types, it is suitable for various concepts mapping with different data types. The experimental results on real-world ontology mapping illustrate the effectiveness of the proposed algorithm.
