The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…

Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)

The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…