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The learning of morphological components in a natural language by means of segmentation of words to identify the prime chores of stems and affixes lead to effective morphological analysis. Morphological segmentation is an important step in the analysis of natural languages to identify its intricate properties. Remarkable approaches been used in order to construct an effective morphological segmentation...
An original model of linguistic summaries extracted from episodic data is briefly presented. In particular, a class of linguistic summaries expressed as modal equivalences is considered. The model is tailored to the concept of autonomous agent systems, and is supported by several detailed, non-technical, natural language processing and knowledge representation theories. Complementary to the well known...
The word lexical in lexical analysis, its meaning is extracted from the word “lexeme”. Lexeme is an abstract unit of morphological analysis in linguistics. A lexical analyser is used in various applications like text editors, information retrieval system, pattern recognition programs and language compilers. But we limit our discussion in this paper to language compilers. Lexical analyser being the...
Decision making has become a core research area in different fields such as evaluation, engineering, medicine, etc. Usually, decision making problems are defined in contexts with vague and imprecise information. The use of linguistic modeling has provided successful results in decision making problems. However, most of the linguistic approaches are limited, because they restrict the elicitation of...
Uncertainty, hesitation and vagueness are inherent to human beings when articulating opinions and preferences. Therefore in decision making situations it might well be the case that experts are unable to express their opinions in an accurate way. Under these circumstances, various families of preference relations (PRs) have been proposed (linguistic, intuitionistic and interval fuzzy PRs) to allow...
For the vague nature of trust and reputation, the traditional reputation modelings used the classic probability or fuzzy sets to describe and measure the degree of trust. The theoretic foundation of these models is subject logic or fuzzy logic. But in some practical applications, the usage of simple probability model led trust's subjectivity and uncertainty to randomness. For the fuzzy logic, the...
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