چکیده مقاله
Sentence Clustering is often used as a first step in document summarization to find redundant information Number of clusters, type and quality of them can have important roles in the automatic text summarization Also the similarity criteria have effective roles in coverage of principal and significant sections of a text In this research, it is tried to use a new approach in the text summarization problem based on PSO Particle Swarm Optimization Similarity of sentences is calculated based on semantic correlations and it is contrary to similarity based on word co occurrences In this research, number of clusters is not considered as a predefined parameter and it is tried to find the optimal cluster numbers The proposed system is evaluated on a large dataset of sports news The results show that the output of this system is more efficient and accurate than similar approaches
کلیدواژهها
نویسندگان
Ali Bazghandi
School of Computer Engineering and IT Shahrood University of Technology Shahrood, Iran
Mehdi Bazghandi
Information Technology Unit Organization of Public Libraries Mashhad, Iran
شیوه ارجاع
Bazghandi, Ali and Bazghandi, Mehdi,1395,Using Semantic PSO Clustering Approach for Automatic Text Summarization,3rd National Congress of Electrical and Computer Engineering of Iran,Tehran
ارائهشده در
مجموعه مقالات سومین کنفرانس سراسری نوآوری های اخیر در مهندسی برق و کامپیوتر19 شهریور 1395 · تهران