Outbound information analysis for generating user interest profiles and improving user productivity

Abstract

A system for automatically generating user interest profiles and delivering information to users learns a user's interests by monitoring the user's outbound communication streams, i.e., the information that the user produces either by typing (e.g., while a user is composing an e-mail message or editing a word processor document) or by speaking (e.g., while a user is engaged in a phone conversation or listening to a lecture). The system uses the monitored text to build (and possibly update) a user interest profile. The profile is constructed from current text generated by the user, so that the retrieved information reflects present user interests. In addition, the profile may also retain past user interests, so that the profile reflects a combination of past and present user interests. The system then automatically queries diverse databases for information relevant to the interest profile. The databases may include internet web pages, files stored on the user's local network, and other local or remote data repositories. The queries may use a combination of internet search engines, the specific selection of which may depend upon the nature and/or content of the queries. The information retrieved in response to the queries is then presented to the user. The retrieved information may contain, for example, answers to questions that the user might ask and/or data related to the user's current and continuing interests. Because a user's current speech or typed text is highly correlated with the user's current interests, the retrieved information will be relevant to the user's actual interests. The communication stream monitoring, interest profile building, data base querying, and presentation of retrieved information are all performed automatically, in real time, and in the background of current user activities.