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Towards everyday language information retrieval systems via minicomputers

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  • Colin Bell
  • Kevin P. Jones

Abstract

Minicomputer‐operated information retrieval (IR) systems are capable of employing relatively advanced methods, some of which are comparable with those employed in main‐frame systems. Many of these systems operate on dedicated machines and can therefore provide very rapid access to information, while remaining under the direct control of an information department. One system has now given over three years of satisfactory operation: this is MORPHS‐Minicomputer Operated Retrieval (Partially Heuristic) System. This system incorporates a number of linguistic features including the ability to find roots of words through affix stripping. Synonyms and compound words can also be handled and several search strategies (including SDI) are available. The latter have been developed considerably since the inception of the system. Consideration is given to the automation of the indexing process which is currently restricted to material for SDI.

Suggested Citation

  • Colin Bell & Kevin P. Jones, 1979. "Towards everyday language information retrieval systems via minicomputers," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 30(6), pages 334-339, November.
    • Handle: RePEc:bla:jamest:v:30:y:1979:i:6:p:334-339
    DOI: 10.1002/asi.4630300606
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    Cited by:

    1. Arno de Caigny & Kristof Coussement & Koen W. de Bock & Stefan Lessmann, 2019. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," Post-Print hal-02275958, HAL.
    2. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan, 2020. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1563-1578.

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