1. A Self-Training Interpretive and Retrieval System for Mass Spectra. The Data Base
- Author
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Akira Tatematsu, Fred W. McLafferty, Kain-Sze. Kwok, R. G. Werth, Ikuo Sakai, M. A. Busch, Rengachari. Venkataraghavan, R. C. Platt, J. W. Serum, Gail M. Pesyna, and B. A. Meyer
- Subjects
Structure (mathematical logic) ,Information retrieval ,Series (mathematics) ,business.industry ,Chemistry ,Line notation ,Pattern recognition ,Base (topology) ,Spectral line ,Data class ,Mass spectrum ,Artificial intelligence ,business ,Self training - Abstract
We have recently described1,2 a self-training interpretive and retrieval system (STIRS) for computer interpretation of mass spectra which utilizes directly data of all available reference spectra, and does not require prior spectra/structure correlations of these data either 'by human or computer effort. The computer selects different classes of data known to have high structural significance, such as characteristic ions, series of ions, and masses of neutrals lost, from the unknown mass spectrum, and matches these against the corresponding data of all the reference spectra. The reference compounds of closest match in each data class are examined for common structural features; criteria have been determined so that such features can 'be identified with approximately 95% relia'bility. Each reference compound has been coded in Wiswesser Line Notation (WLN) to make possible computer recognition of structural features. Further details of the initial system are available.1,2
- Published
- 1974
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