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.

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.