b2c中基于xml的商品评价信息的提取分析word格式论文.docxVIP

AbstractAs the rapid developing of B2C electronic commerce, the information about the introduction and comments of the merchandise on the Web is expanding sharply. For this reason, when the customers shop merchandise on the Internet, they will take much time and energy to look for the information about the comments of the relative merchandise on the electronic commerce webs and forum. Its very inconvenient to customers. On the other side, to the B2C electronic commerce enterprise, its a main task that how to supply right and sufficient information about comments of merchandise to attract and retain the customers.The dissertation reviews the state of Web data extraction and presents a fast applicable Web data extraction method based on XML according to the requirements in B2C electronic commerce. The further study is made for some key technologies, such as search strategy, transformation algorithm and extraction method. We wish to make some contributions for B2C electronic commerce. The main contents of this paper include the followings:First of all, the dissertation presents a modified HITS algorithm in small Web search. According to the characteristic of link structure, we construct implicit links in small Web, and weight links according to how often they were accessed. The new link structure of a small Web is close to that of the global Web, and weight links combine with users?feedback. Theory shows that the modified algorithm is correct.Then, a stack-based HTML to XML transformation approach is put forward. It simplifies data extraction and gets ready for extract appropriate data.After that, the criterion of robust data extraction in XML is proposed. The criterion is applied in XML data extraction: location special area and mapping merging data. Good methods are provided for each. The results show that the methods are effective.In the end, the prototype is designed. Data extraction, XML and Java are comprehensively utilized in the prototype by combining those thr