Mining for interactive identification of users information needs ?
To facilitate searching and navigation, much information has been hierarchically organized into categories with different levels of generality. However, users still suffer information overload in querying a hierarchical information space, since they often cannot make their aspects of interest precise enough. One way to alleviate the problem is to interactively identify those information categories that correspond to the users information needs (INs). In that case, information of interest may be found in a more dedicated space (i.e. subset of categories), promoting both search precision and user satisfaction. This paper presents a technique that employs text mining to build each categorys profile through which users INs may be interactively identified. The profiles are mined incrementally so that the system may adapt to the ever-changing information space. The technique is shown to be effective in mapping users INs to suitable categories without requiring the users to enter long queries, conduct many interactions, and suffer heavy cognitive load. It may serve as an intelligent intermediary in various applications that link users to suitable information categories and service departments.
category profile information need identification profile mining incremental mining