Hot Event Summary on Micro-blog Generated by Multi Model Based on Event Elements postprint

Abstract: [Purpose/significance] In order to help the readers understand the contexts of the news event on micro-blog platform and improve readability and accuracy of micro-blog event summary, we propose a method for extracting the event summary organized by time axis based on event elements.[Method/process] Based on the characteristics of micro-blog text, we combine both advantages and disadvantages of the LDA and mutual information maximum entropy model (MaxEnt-MI) and extract event summary keywords, screening micro-blog with micro-blog communication value and theme relevance and generating event summary in the form of time-keywords-mircro-blog.[Result/conclusion] Comparing with the traditional TextRank method in the artificially labeled test set, we find the F value increased by 8% to 13%, and the internal tests show that the readability of the abstracts is significantly improved. The number of experimental texts and test sets and the richness of the event need to be further expanded, and more weighting strategies should be considered in order to improve the accuracy of the abstracts. The experimental results and the test results show that the proposed method is feasible and effective, which can meet the needs of the users for the hot event summary information, and improve the accuracy of the micro-blog abstract extraction.