Information retrieval systems, by contrast, are designed to respond once to each query based on the contents of a relatively static set of documents. I will address filtering and retrieval from the perspective of text selection because that has been the focus of my research, but I expect that my observations will generalize well to other information filtering problems. Although both text filtering and retrieval draw from a common set of text representation and selection techniques, their differing objectives have implications for user modeling. I will describe one such issue in the hope that our discussion will illuminate other concerns and suggest fruitful directions for further research. It seems to me that the most significant distinction between filtering and retrieval is the duration over which the user's information need must be modeled.
Users have many interests, and the lifetime of a particular interest is subject to wide variability.
For example, a user may have an abiding interest in stock market quotations, while their interest in a news story may be considerably more transitory. Even when interests have long persistence, they may undergo significant changes over their lifetime. Furthermore, these changes may occur either gradually or abruptly. For example, the particular stocks for which a user desires quotations might change abruptly when the user sells all of their shares of that stock. A further complication is that the intensity of an interest may vary over time in a way that is difficult to predict.