Architecting personalized delivery of multimedia information

in fo rmat ion filters are essential mediators between information sources and their users. In most cases, both the information sources and the information users possess no mutual knowledge that can guide them in f inding the informat ion most relevant for the users' momen ta ry and long-term needs. Filters, which are positioned logically as " third parties" to the communicat ion between users and sources, should possess both the knowledge and the functionality to examine the information in the sources and to forward the informat ion "they judge" as relevant to individual users. Informat ion filters can work on behalf of users as well as on behal f of sources. In the first case, which is the most common today, filters assist users in f inding relevant informat ion and overcoming what has been termed "the informat ion flood." In the second case, filters can be used by sources to "target" information to potentially interested users. Curren t ly it appears that m a n y of the research issues involved in the proper design of high-performance filters are addressed only for a specific and relatively narrow class of sources and users. One reason for this is that it is exceedingly difficult at this t ime to provide general-purpose solutions to information-filtering requirements. In the general case, user needs do not seem to lend themselves to precise model ing [1], and information sources do not seem to provide precise enough descriptors of their contents (see [5] and references therein). Given this double imprecision, informat ion filters are being optimized for specific context, specific types of users, and specific sources. In this article, as in [2], we view the information-fil tering process as dependent on the application domain in which it operates and on the context in which it is used. We