Helping people find what they don't know

Communications of the ACM Vol. 43, No. 8 (August 2000), Pages 58-61 Recommendation systems help users find the correct words for a successful search. Imagine you are performing a task while interacting with a service hosted on the Internet or with an automated speech recognition mobile phone service. What if during your interaction with this service, a machine makes a recommendation suggesting how you could better perform your current task? An important problem relating to personalization concerns understanding how a machine can help an individual user via suggesting recommendations. When people engage in information-seeking behavior, its usually because they are hoping to resolve some problem, or achieve some goal, for which their current state of knowledge is inadequate. This suggests they dont really know what might be useful for them, and therefore may not be able to specify the salient characteristics of potentially useful information objects. Unfortunately, typical information systems require users to specify what they want the system to retrieve. Furthermore, people engaging in large-scale information systems typically are unfamiliar with the underlying operations of the systems, the vocabularies the systems use to describe the information objects in their databases, and even the nature of the databases