The Topics of CAAD : A Machine's Perspective

Abstract

Ontology of a scientific field typically includes a taxonomy that breaks up the field into several topics. The break-up is present in the organisation of information in books, libraries and on the Web. An on-line database of papers related to CAAD called CUMINCAD was created and it includes over 3000 papers with abstracts. They are available through the search interface - one knows an author or a keyword and can find the papers where such keyword or author's name appears. Alternative interface would be through browsing papers topic by topic. The papers, however, are not categorised. In this paper, we present the efforts to use the machine learning and data mining techniques to automatically group the papers into clusters and create a set of keywords that would label a cluster. The hypothesis was that an algorithm would create clusters of papers automatically and that the clusters would be similar to the groupings a human would have made. We investigated several algorithms for doing an analysis like that but were unable to prove the original hypothesis. We conclude that it requires more than objective statistical analysis of the words in abstracts to create an ontology of CAAD.