By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP（baek propagation） neural network. By this method, t...By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP（baek propagation） neural network. By this method, the users＇ interest in the WWW cache can be described and the neural network of users＇ interest can be constructed by positive spread of interest and the negative spread of errors. This neural network can infer the users＇ interest. This model is not the simple extension of the simple interest model, but the round improvement of the model and its related algorithm.展开更多
Fuzzy ontologics are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses co...Fuzzy ontologics are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.展开更多
It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing ...It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.展开更多
This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instan...This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instances. It provides the checking based on the weighted mutual instances considering fault tolerance, gives a way to partition the large-scale mutual instances, and proposes a process greatly reducing the manual annotation work to get more mutual instances. Intension annotation that improves the checking method is also discussed. The method is practical and effective to check subsumption relations between concept queries in different ontologies based on mutual instances.展开更多
基金Supported bythe Outstanding Young Young Scientist’s Fund ofthe National Natural Science Foundation of China (60303024) ,the National Natu-ral Science Foundation of China (90412003) , National Grand Fundamental Re-search 973 Programof China (2002CB312000) , Doctor Foundation of Ministry ofEducation(20020286004) , Opening Foundation of Jiangsu Key Laboratory of Com-puter Information Processing Technology in Soochow University, Natural ScienceResearch Planfor Jiang Su High School(04kjb520096) ,Doctor Foundatoin of Nan-jing University of Posts and Telecommunications(2003-02)
文摘By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP（baek propagation） neural network. By this method, the users＇ interest in the WWW cache can be described and the neural network of users＇ interest can be constructed by positive spread of interest and the negative spread of errors. This neural network can infer the users＇ interest. This model is not the simple extension of the simple interest model, but the round improvement of the model and its related algorithm.
基金Supported by the National Natural Science Foundation of China(60373066 , 60425206 , 90412003) , National Grand Fundamental Research 973Programof China(2002CB312000) , National Research Foundationfor the DoctoralProgramof Higher Education of China (20020286004)
文摘Fuzzy ontologics are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.
基金Supported by the National Natural Science Foundation of China (60503020, 60503033, 60373066, 60403016)Opening Foundation of Jiangsu Key Laboratory of Computer Information Processing Technology in Soochow University
文摘It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.
基金Supported by the National Natural Sciences Foundation of China(60373066 ,60425206 ,90412003) , National Grand Fundamental Research 973 Pro-gramof China(2002CB312000) , National Research Foundation for the Doctoral Pro-gramof Higher Education of China (20020286004)
文摘This paper proposes a checking method based on mutual instances and discusses three key problems in the method： how to deal with mistakes in the mutual instances and how to deal with too many or too few mutual instances. It provides the checking based on the weighted mutual instances considering fault tolerance, gives a way to partition the large-scale mutual instances, and proposes a process greatly reducing the manual annotation work to get more mutual instances. Intension annotation that improves the checking method is also discussed. The method is practical and effective to check subsumption relations between concept queries in different ontologies based on mutual instances.
