Exploiting contextual change in context-aware retrieval

Abstract

Information retrieval systems are usually unaware of the context in which they are being used. We believe that exploiting context information to augment existing retrieval methods can lead to increased retrieval precision. This approach is particularly important with the development of wireless mobile information appliances, such as PDAs. Many of these devices are aware of the user's physical context, and this has led to the evolution of context-aware applications. Such applications can automatically utilise the user's current context, e.g. location or ambient temperature. Context-Aware Retrieval is related to traditional Information Retrieval and Information Filtering, but is potentially more challenging due to the often continuous changes in user context. To meet these challenges we suggest a potential advantage of Context-Aware Retrieval: this is that the current context is often changing gradually and semi-predictably. In this paper we suggest new methods based on a context-diary and caching aimed at improving both the precision of relevant retrieved information and the speed/availability of retrieval. The methods can be used, in principle, on top of existing retrieval systems.