There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomp...There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomplete knowledge is proposed. First, the calculation principle of the attribute weight of the ontology concept is presented, and the calculation function of the attribute weight is derived through experiments. Then, the membership degree of the incomplete individual to the concept is computed. Finally, the incomplete individual is classified according to the principle of the variable precision rough set model. The experimental results show that the average precision of the classification of the incomplete individuals is 81.7% when the common attributes are omitted and that it is difficult to classify the incomplete individuals correctly when the private attributes are omitted. This method is significant for handling incomplete knowledge in the process of ontology construction.展开更多
In order to recognize one＇s intention from the communication, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of cha...In order to recognize one＇s intention from the communication, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. This paper analy- zes emotion category according to the statistics of Affective Word （AW） hierarchy and descries an e- motion ontology from Chinese knowledge resource semi-automatically created for human machine in- teraction. The emotion hierarchy is called complex emotion. Firstly, over 7 000 AWs have been annota- ted and theft detailed explanations had been collected for an affective lexicon and then the consistent rela- tionships are automatically parsed and a serial of e- motion hierarchical structures are built up. More than 50 affective categories are extracted by a lexical clustering algorithm and about 5 000 nouns and ad- jectives and 2 000 verbs are categorized into the predicate hierarchy. The results have been evaluated to be valid by two metrics.展开更多
基金supported by the Beijing Natural Science Foundation under Grant No.4123094 the Science and Technology Project of Beijing Municipal Commission of Education under Grants No.KM201110028020,No. KM201010028019 Beijing Key Construction Discipline“Computer Application Technology”
文摘There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomplete knowledge is proposed. First, the calculation principle of the attribute weight of the ontology concept is presented, and the calculation function of the attribute weight is derived through experiments. Then, the membership degree of the incomplete individual to the concept is computed. Finally, the incomplete individual is classified according to the principle of the variable precision rough set model. The experimental results show that the average precision of the classification of the incomplete individuals is 81.7% when the common attributes are omitted and that it is difficult to classify the incomplete individuals correctly when the private attributes are omitted. This method is significant for handling incomplete knowledge in the process of ontology construction.
基金supported by the Ministry of Education,Science,Sports and Culture,Grant-in-Aid for Scientific Research under Grant No.22240021the Grant-in-Aid for Challenging Exploratory Research under Grant No.21650030
文摘In order to recognize one＇s intention from the communication, both the meaning and the emotion are necessary to be interpreted correctly. But until now the study of fine-grained theory of emotion is still full of challenges. This paper analy- zes emotion category according to the statistics of Affective Word （AW） hierarchy and descries an e- motion ontology from Chinese knowledge resource semi-automatically created for human machine in- teraction. The emotion hierarchy is called complex emotion. Firstly, over 7 000 AWs have been annota- ted and theft detailed explanations had been collected for an affective lexicon and then the consistent rela- tionships are automatically parsed and a serial of e- motion hierarchical structures are built up. More than 50 affective categories are extracted by a lexical clustering algorithm and about 5 000 nouns and ad- jectives and 2 000 verbs are categorized into the predicate hierarchy. The results have been evaluated to be valid by two metrics.
