Intelligent Text Handling Using Default Logic

There is a need to develop more intelligent means for handling text in applications such as information retrieval, information filtering, and message classification. This raises the need for mechanisms for ascertaining what an item of text is about. Even though natural language processing offers the best results, it is not always viable. A less accurate, but more viable alternative, is to reason with keywords in the text. Unfortunately, classical reasoning is often inadequate for determining from some keywords what a text is about. In particular, it does not allow context-dependent interpretation of keywords. So for example, if some text has the keyword oil, it is usually also about minerals, though with exceptions such as when it has the keyword cooking. To address this kind of problem, we consider a model of “aboutness” based on default logic.