THE CREATION OF NEW KNOWLEDGE BY INFORMATION RETRIEVAL AND CLASSIFICATION

Abstract

Knowledge can be created by drawing inferences from what is already known. Often some of the requisite information is lacking and has to be gathered by whatever research techniques are appropriate, e.g. experiments, surveys etc. Even if the information has all been published already, unless it is retrieved no inferences will be drawn from it and consequently there will exist some knowledge that is implicit in the literature and yet is not known by anyone. This ‘undiscovered public knowledge’, as it is termed by Swanson, may exist in the following forms: (i) a hidden refutation or qualification of a hypothesis; (ii) an undrawn conclusion from two or more premises; (iii) the cumulative evidence of weak, independent tests; (iv) solutions to analogous problems; (v) hidden correlations between factors. Methods of classification may also play a direct role in the creation of original knowledge. Novel solutions to problems may be discovered by generating different combinations of the basic features of the solutions, as is done in morphological analysis. Alternatively a natural classification may identify gaps in existing knowledge. This paper reviews previous work on producing knowledge by information retrieval or classification and describes techniques by which hidden knowledge may be retrieved, e.g. serendipity in browsing, use of appropriate search strategies and, possibly in the future, methods based on Farradane's relational indexing or artificial intelligence.