Application Study Of Lucene Full-text Retrieval On The Network Education Platform

With the prevalence of the internet, there brings lots of web page information, kinds of education resources and electronic information carriers. Large quantities of information and resources are the wealth of the school, so it's very important to make full use of all kinds of education resources. Therefore, it is necessary to study and design a full-text retrieval system for kinds of resources on the the network education platform.The thesis analyzes the shortage of the present network education resource retrieval system, and probes a search engine combining the custom-built full-text retrieval engine with the network education platform. The paper brings forward a new conception for the first time, optimizes Chinese word segmentation combination which makes the analysis of the query request more thorough and the searching results more accurate and more flexible. The paper succeeds to extract text from different kinds of education resources, such as the extraction of HTML PDF Office Text DB etc, and then switch them into fixed structure to establish index to support the full-text retrieval for all kinds of resource on network education platform.Besides,the paper adopts the optimized renew strategy that is to combine the automatical index and handiwork index, which makes the renew strategy more intellective.The paper introduces principle of some key technologies, such as Struts frame and Lucene, a full-text retrieval engine toolkit. According to the requirement of the platform, the paper uses UML to describe functional module and some main programs of the full-text retrieval system, including series of software life cycle stages: content organization, overall design, UML modeling, function enablement by Struts, test and release.