The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships, and the safety of navigation. This paper proposes an ontology-based fuzzy support agent for ship steering control and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system based on linguistic ins...

The safety of cruise passengers is a key element for a cruise company. Among various aspects, the ability to interpret and recognize cruisers’ emotions, so that he/she feel safe, plays a central role in human communication. Affective computing addresses the computational processing of emotions. Current automatic emotion recognizers basically use automated classification tools to label emotions ...

Fuzzy Description Logics (DLs) are logics that allow to deal with vague structured knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing fuzzy ontologies has received no attention so far. We report here our preliminary investigation on this issue by describing ...

In this work, a concept representation model (FISCRM) has been developed, which is based on two types of fuzzy interrelations between words, synonymy and generality, obtained from a fuzzy dictionary of synonyms [1] and a fuzzy ontology respectively. The model has been put into the metasearcher FISS (Fuzzy Interrelations and Synonymy based Searcher) which is able to retrieve groups of web pages ...

Fuzzy Description Logics (DLs) are logics that allow to deal with vague structured knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing fuzzy ontologies has received very little attention so far. We report here our preliminary investigation on this issue by de...

In this paper, we present a method of an ontology mapping based on a similarity measure and Fuzzy logic in order to classify (i) the similarity of the ontology structure of learning object repositories and (ii) LOR which stores metadata of learning objects based on our ontology model. In this model, values of the ontology similarity are computed for concepts, properties, and relations. The onto...

Fuzzy Description Logics are logics which allow to deal with structured knowledge affected by vagueness. Although a relatively important amount of work has been carried out in the last years, fuzzy DLs are open to be extended with several features worked out in other fields. In this work, we start addressing the problem of incorporating Multi-Criteria Decision Making (MCDM) into fuzzy Descripti...

e-Learning; Fuzzy domain ontology; Cross ontology; Semantic similarity measure Abstract e-Learning is one of the most preferred media of learning by the learners. The learners search the web to gather knowledge about a particular topic from the information in the repositories. Retrieval of relevant materials from a domain can be easily implemented if the information is organized and related in ...

In this paper we present an approach to use fuzzy logic and data mining techniques in order to improve the quality of intelligent agents services in the Internet context. The overall objective is to design and implement a software model for collaborative environments capable of extracting knowledge from newsgroups, chat services ... The construction of the components of this software model is m...

By the development of Semantic Web, increasing demands for vague information representation have triggered a mass of theoretical and applied researches of fuzzy ontologies, whose main logical infrastructures are fuzzy description logics. However, current tableau algorithms can not supply complete reasoning support within fuzzy ontology: reasoning with general TBox is still a difficult problem i...