Design And Research Of Personalized Automatic Abstracting

With the popularization of the internet, the network has become a huge information resource. The large amounts of information not only provides us with the facilitate information resource, but also brings us a problem that how to get effective information from the internet. The automatic abstracting technology is a natural language processing topic. It automatically produces the article's summarization which can basically reflect the article's information and save users'searching time. Two key technologies in automatic abstracting are introduced. The first one is discourse segmentation which is an important automatic abstracting technology. It divides the article into several parts according to the subjects in the article. On the foundation of the predecessor's works, to the lake of semantic analyzing in traditional TextTiling algorithm based on terms, concept expansion to terms based on the HowNet is taken and compact computation through the concept is made. The experimental result indicates that the TextTiling algorithm based on the concept expansion can get higher accuracy. The second one is the sentence estimation problem in automatic abstracting. By analyzing the shortage and advantage of the traditional automatic abstracting method based on terms computation and the traditional automatic abstracting method based on article grammar structure analyzing, chunks to the rule groups are built up, furthermore works of sentence processing and computation based on chunks are introduced. Experimental results show that, the summarization's quality by the chunk computation method is improved noticeably. Finally, a system of personalized automatic abstracting is introduced. The system constructure and the computation method are showed,furthermore the summarization according to the user's interest is produced. The experimental result indicates that, automatic abstracting based on users' interesting analyzing can finely meet users' needs.