A common practice for resolving connicts among a group of agents is to let the majority decide. We formalize this principle and apply it to the problem of merging the knowledge of multiple agents. We then postulate logical properties that all knowledge merging operators should satisfy and give a model-theoretic characterization of all merging operators that satisfy the postulates. It turns out ...

It is well known that the minimal change principle was widely used in propositional knowledge base updates. However, recent research has shown that under some circumstances, the conventional minimal change methods were inappropriate for updating knowledge bases with disjunctive eeects. In this paper we propose a new method for the knowledge base update based on a persistence principle, which pr...

KBMSs for natural language knowledge will be fundamental components of knowledgeable environments where non-computer professionals can use various kinds of support tools for document preparation or translation. However, basic models for such KBMSs have not been established yet. Thus, we propose a model for an LKB focusing on dictionary knowledge such as that obtained from machine-readable dicti...

Our work develops a new methodology and tool for the validation of probabilistic knowledge bases throughout their lifecycle. The methodology minimizes user interaction by automatically modifying incorrect knowledge; only the occurrence of incomplete knowledge involves interaction. These gains are realized by combining and modifying techniques borrowed from rulebased and artificial neural networ...

In the field of Artificial Intelligence (AI) there exists a long-standing goal for an expert system. Intelligent Query Processing is concerned with in the context of automatically processing NL text query with several Knowledge Base (KB) technique of AI-literature to develop an expert system. An intelligent system requires understanding of related terms like wisdom, knowledge, reasoning, though...

Knowledge base building environments must progress in two important directions: (i) increased participation of domain experts in the knowledge design process through new computational models and effective man-machine interfaces; and (ii) automated knowledge acquisition tools to facilitate the overt expression of knowledge. This paper presents the integration of a knowledge acquisition methodolo...

Although an increasing number of RDF knowledge bases are published, many of those consist primarily of instance data and lack sophisticated schemata. Having such schemata allows more powerful querying, consistency checking and debugging as well as improved inference. One of the reasons why schemata are still rare is the effort required to create them. In this article, we propose a semi-automati...

This paper presents a hierarchical heterogeneous knowledge-base model. The model is designed to support manipulation with human knowledge about real or abstract concepts from the real world that are uncertain, ambiguous, vague and fuzzy. It has two levels: a lower associative and a higher semantic. It enables processing of novel concepts in the inheritance and the recognition inference processe...

The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionisticand interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these ideas the concept of multivalued knowledge-b...