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Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Abstract Machine Learning: A Guide to Current Research provides a collection of current research papers mostly collected form participants at the Third International Machine Learning Workshop held in 1985. These 77 separate papers were collected and reformatted at Rutgers to produce a consistent format and a common bibliography. The range of learning topics include (taken from the preface): analogy, conceptual clustering, explanation-based generalization, incremental learning, inductive inference, learning apprentice systems, machine discovery, theoretical models, and applications. All of these topics, except incremental and apprentice systems are included as heading in the index. Other useful index headings include research institution (a few are missing, primarily those where the several authors are from more than one place) and program name. The papers are short; the average length of five pages per paper, based on the number of papers and the length of the book, overstates their length because of blank pages due to formatting considerations. In the short space for each paper it is not possible to explain in detail how anything is done. There is space only to say what is being done by the system. Thus, the bibliographic references become important for a deeper understanding of individual techniques.
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Book Review
Publisher Date 1973-08-01
Publisher Place New York
Journal ACM SIGART Bulletin (SGAR)
Issue Number 103
Organization Price, Keith


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Source: ACM Digital Library