A Fuzzy Fusion Framework for Generating Purpose-oriented Texts

Fusing textual information, as type of information fusion, has been great significance to those interested in making informative texts out the existing ones. The main idea behind text like any other is merge partial from different sources such a way that outcome can hold reasonably high relevance with regard certain objectives. In this paper, fuzzy framework proposed for generation, according which range relevant are merged yield producing new help users fulfill functionality plausible manner. focal point our approach fusion distance between class prototype on one side and feature vectors belonging subsets side. Results experiments, show suggested be suitable alternatives performing cases identity viewpoint considered unclear. This would turn into an effective utilization purpose generating texts.