Information Filtering and Personalization in Databases Using Gaussian Curves

We present an information filtering and adaptive personalisation algorithm for arbitrary information systems based on databases. This algorithm is called GRAS (Gaussian Rating Adaptation Scheme), and it combines content-based and collaborative filtering. The goal is to filter retrieved documents of a query according to the personal interest of a user and to sort them according to the personal relevance. The algorithm tries to make the benefits of collaborative filtering available to application domains where collaborative filtering could not yet be applied due to lack of the critical mass of users or improper content structure. The algorithm collects background information about the user and the content by implicit and explicit feedback techniques. This information is then used to consecutively adapt userand object profiles according their maturity. The described algorithm is applicable for the personalisation of any kind of application domain, even on multimedia data. GRAS is implemented in the multimedia database MultiMAP1 as a generic personalisation provider module.