Automatic Indexing From Machine Readable Abstracts Of Scientific Documents
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Automatic Indexing from Machine Readable Abstracts of Scientific Documents
State-of-the-art of machine indexing is reported. Various proposed machine indexing methods are reviewed and evaluated. Methods for comparing machine and human indexing as well as machine indexing systems among themselves are described. Possible approaches to various problem solutions in machine indexing are indicated. The report describes the design of the Formal Autoindexing of Scientific Texts (FAST) system. Characteristics of Uniterm co- ordinate indexes are investigated and generalizations to scientific indexes made. Laws for the formation of words in the indexing language are derived and verified. The operational principles of the FAST system and test results of various system components are reported. Indexes produced by the FAST method are compared with those produced by human indexers for inter-indexer and intra- indexer consistency. A method of formal evaluation of indexes using the information theory approach is presented and applied to the FAST and conventional indexes. It is concluded that the FAST system can produce Uniterm co-ordinate indexes adequate to user's requirements better and faster than human indexers can do.