A Domain Division Method of Volunteer Service Project Based on Improved Attention Mechanism Model

Text classification plays a vital role in natural language processing, enabling the learning of complex features within texts and efficiently automating their categorization. The textual data of volunteer service project serves as a crucial criterion for domain delineation. Utilizing text classification technology enables the identification of latent features within the text, thereby facilitating policy analysis and formulation. In this paper, we propose a multi-dimensional attention mechanism-based text classification algorithm, tailored to the structural characteristics of volunteer service text data. By segmenting the text structure, the algorithm independently extracts features from different sections and employs an attention mechanism model to integrate and predict the results. Experimental comparisons with existing common classification algorithms have validated the superiority of our approach in the domain delineation of volunteer service project.