I-struve: Automatic linguistic descriptions of visual double stars

New technologies allow human beings to acquire huge amounts of information about their physical environment. Currently the challenge consists of automatically interpreting this information providing each specific user with descriptions remarking the relevant and hiding the irrelevant according to her/his specific goals. omy is a traditional field of human exploration. Within this field, we focus on observation of double stars. About half of the stars in our Milky Way are double or multiple stars. These celestial objects are observed by both professional and amateur astronomers. These experts usually take notes of relevant features by generating textual reports that contain descriptions of their perceptions. s paper, we present last results on our research in Computational Theory of Perceptions. We describe a computational system able to automatically generate simple linguistic descriptions of double stars from certain numerical physical measures. These linguistic summaries make data more accessible to people and create new possibilities of data management. We include several examples and analysis of the obtained results.