1. ABSTRACT A SIMPLE PROBABILISTIC APPROACH TO CLASSIFICATION AND ROUTING

Several classification and routing methods were im-plemented and compared. The experiments used FBIS documents from four categories, and the measures used were the ff.idf and Cosine similarity measures, and a maximum likelihood estimate based on ass~lming a Multinomial Distribution for the various topics (popula-tions). In addition, the SMART program was run with 'lnc.ltc ' weighting and compared to the others. Decisions for both our classification scheme (docu-ments are put into any number of disjoint categories) and our routing scheme (documents are assigned a 'score ' and ranked relative to each category) are based on the highest probability for correct classification or routing. All of the techniques described here are fully automatic, and use a training set of relevant documents to produce lists of distin~i~hin £ terms and weights. All methods (ours and the ones we compared to) gave excel-lent results for the classification task, while the one based on the Multinomial Distribution produced the best results on the routing task