Research On Personalized Document Retrieval Technology

Information retrieval is the process of building up and storing information according to certain ways, and finding the information that users need. With the development of information technology and the spread of Internet world widely, the traditional retrieval tools can't meet the demands of people any more. We are looking for the information resources in Internet more and more. In all kinds of information retrieval tools, search engines are used pretty widely, but the existing search engines is for all users, which can't satisfy the user's individual demands. Personalized information service system can satisfy the users'individual demands effectively.In most retrieval systems, the demand of users is represented by query keywords. In fact, there exists difference between the real demand of users and the query keywords. How to decreasing the difference is the key problem in implementing the user-oriented personalized information service system. We put forward a way of query expansion oriented to user and adapted modification model based on users'interest. Furthermore, the model can use the regulating factorα,β,γ,λto optimize query ,in order to increase the retrieval precision and make the returning documents satisfy users better.In view of the situation that existing search engines have low precision and low recall in document retrieval, this paper proposes a personalized document retrieval system based on the user's interest model. The idea of design is: when every registration of users, we request the user provides his basic information, interest domain, query keywords and so on. We will create an initial user's interest model to every new user according to the basic information. The system will recommend the lately retrieval results for the user automatically after he login in it successfully. User can also carry on his query if he wants. Meanwhile, user can browse or download the documents which he is interested in. The personalized document retrieval system will modify the user's interest model and expand the original query by the result of user feedback automatically, so that the interest model can really represent the user's interest and then improve the precision and recall in searching information.