Natural Language Information Formatting: The Automatic Conversion of Texts to a Structured Data Base

Abstract

The field of computerized language processing encompasses a wide range of goals and methodologies, ranging from such theoretical objectives as the modeling of human linguistic behavior and human language acquisition , to such goals as machine translation , natural language systems for man–machine communication, and speech recognition. What unites these varied endeavors is the need to come to grips with the special features of natural language as a communication system. The chapter approaches the problems from the viewpoint of information science, with applications envisioned primarily in science information retrieval and data base management. The chapter also attempts to provide a general solution to the following problem: Given a collection of documents on a particular subject written in English or another natural language, how can computer programs arrange the information contained in the documents so that it can be accessed from different points of view for a variety of informational tasks. This assumes that there are underlying common features in the texts that can be made explicit by formal procedures. For the field of information management the solution to this problem would extend the data bases on which data processing functions that have already been automated can operate. The chapter discusses the principles and methods of analysis, and computer programs for information formatting. If indeed it is possible to obtain structured data bases from textual material, then the potential for new computer applications is large. In this section a few applications are sketched with reference to how they would be realized on a data base of computer-formatted medical records.