Research On The Web Information Extraction Based Personalized Information Service And Its Implementation

The Internet enriches sources of information for people. However, due to the heterogeneity and lack of structure of Web information resources, people often feel very difficult to find information they need from Internet. Current systems for information service, like search engines and Web Service integration systems, often have limitations in accuracy and coverage, which can not satisfy pepople's growing needs for information.At present, the lager amount of information on the Web is stored in HTML documents.In this dissertation, we firstly analyze the Web information extraction technology, and then present WINIS, a framework for web information extraction based personalized information service. Aimed at the rich information hidden in the database of web site(also called the Deep Web), WINIS retrieves it by Web information extraction and provides personalized information service to end users, for whom it is not necessary to know where and how to get the information they need.WINIS is composed of Personalized Service Layer and Web Information Extraction Layer. In the Personalized Service Layer, predefined task shema is used to decompose user's request and a user goal based method for answer composition is proposed. In the Web Information Extraction Layer, an ontology based approach for Deep Web information extraction is presented to retrieve information from Deep Web. This approach extracts data from Deep Web sources effectively and automatically and it solves the key problems of current approaches, such as too much interaction with users, lack of semantic support and process for getting the pages.By using WINIS framework as guidance, we built a prototype system of E-Planning. The experiments show that WINIS based E-Planning system performs well in data extraction, result plan generation and also in expansibility, which indicate the validity of WINIS framework.