A probabilistic model of keyword indexing is outlined, and some of the consequences of the model are examined. An algorithm defining a measure of indexability is developed--a measure intended to reflect the relative significance of words in documents. (Author)

Describes the two basic approaches to the calculation of term discrimination values for automatic indexing. The results of an experiment that investigated the differences between algorithms of these two approaches in terms of their impact on the discrimination value model are reported and discussed. (13 references) (Author/CLB)

Discusses the effect of including relevance data on the calculation of term discrimination values in bibliographic databases. Algorithms that calculate the ability of index terms to discriminate between relevant and non-relevant documents are described and tested. The results are discussed in terms of the relationship between term frequency and…

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…

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…