Research on the Classification Algorithms for the Classical Poetry Artistic Conception based on Feature Clustering Methodology

Abstract

From ancient to nowadays, myriad literati and poets had wrote many popular works, these works is the pearl of Chinese literature and treasures of traditional culture. Due to the length limit of classical poetry, there often appear a lot of allusions. In this paper, we conduct theoretical analysis and numerical simulation on the classification algorithms for the classical poetry artistic conception based on feature clustering methodology. Artistic conception of Chinese classical poetry is an important aesthetic category in the theory which is also an important topic of Chinese traditional aesthetics. It is necessary to improve the classical text classification model and then applied to the classification of Chinese classical poetry. By a large number of classical poetry can be found after reading and classical Chinese poems are often not directly ventilation thought emotion. Our proposed method performs well in the experimental section.