Up to now, no satisfactory theory has been established for formalizing incomplete knowledge in incomplete databases. In this paper, we clarify why existing closed world approaches, such as the CWA, the GCWA, the ECWA,...Up to now, no satisfactory theory has been established for formalizing incomplete knowledge in incomplete databases. In this paper, we clarify why existing closed world approaches, such as the CWA, the GCWA, the ECWA, circumscription, predicate completion and the PWA, fail to do so, and propose a new method. The method is an augmentation of both the ECWA and circumscrip- tion with the mechanism to discriminate implicitly expressed positive knowledge, negative knowledge and truly unknown knowledge.展开更多
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
It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge re...It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge reduction in incomplete infolvnation systems from the information view of rough set theory. First, by extending information entropy-based measures in complete information systems, two new measures of incomplete entropy and incomplete conditional entropy are presented for incomplete information systems. And then, based on these measures the problem of knowledge reduction in incomplete information systems is analyzed and the reduct definitions in incomplete information system and incomplete decision table are proposed respectively. Finally, the reduct definitions based on incomplete entropy and the reduct definitions based on similarity relation are compared. Two equivalent relationships between them are proved by theorems and an in equivalent relationship between them is illustrated by an example. The work of this paper extends the research of rough set theory from information view to incomplete information systems and establishes the theoretical basis for seeking efficient algorithm of knowledge acquisition in incomplete information systems.展开更多
文摘Up to now, no satisfactory theory has been established for formalizing incomplete knowledge in incomplete databases. In this paper, we clarify why existing closed world approaches, such as the CWA, the GCWA, the ECWA, circumscription, predicate completion and the PWA, fail to do so, and propose a new method. The method is an augmentation of both the ECWA and circumscrip- tion with the mechanism to discriminate implicitly expressed positive knowledge, negative knowledge and truly unknown knowledge.
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Sponsored by the Youth Natural Science Foundation of Yantai Normal University.
文摘It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge reduction in incomplete infolvnation systems from the information view of rough set theory. First, by extending information entropy-based measures in complete information systems, two new measures of incomplete entropy and incomplete conditional entropy are presented for incomplete information systems. And then, based on these measures the problem of knowledge reduction in incomplete information systems is analyzed and the reduct definitions in incomplete information system and incomplete decision table are proposed respectively. Finally, the reduct definitions based on incomplete entropy and the reduct definitions based on similarity relation are compared. Two equivalent relationships between them are proved by theorems and an in equivalent relationship between them is illustrated by an example. The work of this paper extends the research of rough set theory from information view to incomplete information systems and establishes the theoretical basis for seeking efficient algorithm of knowledge acquisition in incomplete information systems.
