Knowledge representation and indexing using the unified medical language system.

Ontologies and semantic frameworks can be used to improve the accuracy and expressiveness of natural language processing for the purpose of extracting meaning from technical documents. This is especially true when a rich ontology such as the Unified Medical Language System (UMLS) is available. This paper reports on some tools being developed to make this possible and on some experience with a user interface based on ontologies and semantic networks that allows for interactive knowledge exploration.

Creating a knowledge base of biological research papers.

Intelligent text-oriented tools for representing and searching the biological research literature are being developed, which combine object-oriented databases with artificial intelligence techniques to create a richly structured knowledge based of Materials and Methods sections of biological research papers. A knowledge model of experimental processes, biological and chemical substances, and analytical techniques is described, based on the representation techniques of taxonomic semantic nets and knowledge frames. Two approaches to populating the knowledge base with the contents of biological research papers are described: natural language processing and an interactive knowledge definition tool.

A stochastic interpretation of the Riemann zeta function.

We give a stochastic process for which the terms of the Riemann zeta function occur as the probability distributions of the elementary random variables of the process.

Database techniques for biological materials & methods.

The Biological sciences produce an enormous research literature every year. Research papers are highly structured documents whose content is not captured using the traditional techniques of information retrieval: keywords and flat text. This is especially true of the Materials & Methods section of experimental papers.