Application of a Fuzzy Ontology to News Summarization PROJECT TITLE : A Fuzzy Ontology and Its Application to News Summarization ABSTRACT: A fuzzy ontology and its application to news summarization are presented in this project. Domain ontology with crisp concepts has been extended to include fuzzy ontology with fuzzy concepts as a subset. Uncertainty reasoning problems can be solved by using domain knowledge rather than domain ontology. To begin, domain experts have created an ontology of news events. Preprocessing will generate meaningful terms from news corpus and domain expert-defined Chinese news dictionary. The term classifier will then sort the meaningful terms based on the news's events. Each fuzzy concept in the fuzzy ontology will have a membership degree generated by the fuzzy inference mechanism. Each fuzzy concept has a set of membership degrees linked to different domain ontology events. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Python Data Mining Projects Python Testing Projects Python Artificial Intelligence Projects Disease Prediction Using a Linear Model Based on Principal Component Analysis Application of Text Classification and Clustering of Twitter Data for Business Analytics - 2018