The Application and Problem Analysis of Computer Technology in English Information Processing

Abstract

The traditional method of automatic summarization is based on the statistical extraction of abstract sentences from the grammar, without semantic analysis of the text, resulting in low summarization accuracy. In order to overcome the shortcomings of traditional methods, this article proposes an automatic summarization method based on topic concepts. An English automatic summarization system is designed and implemented based on concept statistics and analytic hierarchy. Concept statistics replace traditional word frequency statistics, based on the main super The concept constructs a vector space model, calculates the importance of the sentence, selects the distribution of the main super concept on the concept hierarchy tree, analyzes the text structure and divides the meaning block, and extracts the abstract with the meaning block as the unit. Preliminarily solved the problem of unbalanced abstract structure of multi-topic articles. The experimental results show that through the methods of concept statistics and semantic hierarchy analysis, the abstracts generated by the English information processing system are more accurate and reflect the main content of the original text more comprehensively.