Personalized Service Technology And Application In Textile Fabric Public Service Platform

With the fast development of Internet and explosive growth of Information, how to provide Information for users timely and properly has attracted more attention. Personalize service has realized the objective of "information finding people", which makes information serve people forwardly. At present, personalized service has been widely applied in E-commerce, finance, Web search, digital library, long-distance education and other fields. However, because of the complicated background of textile industry, personalized service hasn't been applied to textile professional field very well. The textile fabric public service platform faces small-scale and medium-scale textile fabric enterprises and enterprises within supply-and-demand chain, providing professionary information and services of textile. Therefore, personalized service can be used in textile fabric public service platform.Firstly, based on the feature of software structure in textile fabric public service platform, we design a personalized service software module. Then, as the existing recommendation systems can not effectively deal with recommendation issues of the supply-and-demand relation occurred in different kinds of enterprises, we propose a personalized recommendation model based on supply-and-demand relation in textile fabric public service platform, and improve the collaborative filtering technology. By establishing enterprise user groups, the model reduces the quantity of user groups during collaborative filtering, decreases the dimensionality of attributes space when computing, and eventually increases the efficiency of recommendation. Finally, considering the feature of meta-search engine, personalized search engine, and users' search demand of professional field; we propose a personalized meta-search engine faced to textile professional field. Users' professional and personalized needs can be well resolved by analyzing users' searching demand through users' personalized interest database and specialized textile dictionary. Meanwhile, the coverage rate and accurate rate have been greatly improved.