{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T07:52:09Z","timestamp":1767772329718,"version":"3.48.0"},"reference-count":59,"publisher":"Maximum Academic Press","issue":"3","license":[{"start":{"date-parts":[[2009,7,7]],"date-time":"2009-07-07T00:00:00Z","timestamp":1246924800000},"content-version":"unspecified","delay-in-days":6153,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The Knowledge Engineering Review"],"published-print":{"date-parts":[[1992,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>A unifying framework for concept-learning, derived from Mitchell's Generalization as Search-paradigm, is presented. Central to the framework is the generic algorithm Gencol. Gencol forms a synthesis of existing concept-learning algorithms as it identifies the key issues in concept-learning: the representation of concepts and examples, the search strategy and heuristics, and the operators that transform one concept-description into another one when searching the concept description space. Gencol is relevant for practical purposes as it offers a solid basis for the design and implementation of concept-learning algorithms. The presented framework is quite general as seemingly disparate algorithms such as TDIDT, AQ, MIS and version spaces fit into Gencol.<\/jats:p>","DOI":"10.1017\/s0269888900006366","type":"journal-article","created":{"date-parts":[[2009,7,7]],"date-time":"2009-07-07T09:34:48Z","timestamp":1246959288000},"page":"251-269","source":"Crossref","is-referenced-by-count":8,"title":["A unifying framework for concept-learning algorithms"],"prefix":"10.48130","volume":"7","author":[{"given":"Luc","family":"de Raedt","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maurice","family":"Bruynooghe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"27968","published-online":{"date-parts":[[2009,7,7]]},"reference":[{"key":"S0269888900006366_ref057","unstructured":"Vere SA , 1975. \u201cInduction of concepts in the predicate calculus\u201d, In Proceedings of the 4th International Joint Conference on Artificial Intelligence pp 282\u2013287, Morgan Kaufmann."},{"key":"S0269888900006366_ref051","first-page":"167","volume-title":"Machine Learning: an artificial intelligence approach","volume":"2","author":"Sammut","year":"1986"},{"volume-title":"Inductive Logic Programming","year":"1992","author":"Sablon","key":"S0269888900006366_ref050"},{"key":"S0269888900006366_ref046","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116251"},{"key":"S0269888900006366_ref044","doi-asserted-by":"crossref","unstructured":"Muggleton S and Buntine W , 1988. \u201cMachine invention of first order predicates by inverting resolution\u201d. 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Interactive Concept-Learning PhD thesis, Department of Computer Science, Katholieke Universiteit Leuven."},{"key":"S0269888900006366_ref011","unstructured":"Declercq E , 1990. Een uitwerking van het generisch algoritme Gencol dat concepten leert, Master's thesis, Department of Computer Science, Katholieke Universiteit Leuven (in Dutch)."},{"key":"S0269888900006366_ref009","first-page":"31","volume-title":"Proceedings of the 2nd European Working Session on Learning","author":"Cestnik","year":"1987"},{"key":"S0269888900006366_ref008","volume-title":"A comparative study of the representation languages used in the Machine Learning Toolbox","volume":"90","author":"Causse","year":"1990"},{"key":"S0269888900006366_ref040","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-12405-5"},{"key":"S0269888900006366_ref007","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(88)90001-X"},{"key":"S0269888900006366_ref006","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(85)90052-9"},{"volume-title":"Pattern-directed inference Systems","year":"1978","author":"Buchanan","key":"S0269888900006366_ref005"},{"volume-title":"Kardio: a study in deep and qualitative knowledge for expert Systems","year":"1989","author":"Bratko","key":"S0269888900006366_ref004"},{"volume-title":"Fundamentals of Artifidal Intelligence","year":"1986","author":"Biermann","key":"S0269888900006366_ref003"},{"key":"S0269888900006366_ref002","doi-asserted-by":"publisher","DOI":"10.1145\/356914.356918"},{"volume-title":"Interactive Theory Revision: an inductive logic programming approach","year":"1992","author":"De Raedt","key":"S0269888900006366_ref013"},{"key":"S0269888900006366_ref034","volume-title":"Machine Learning: an artificial intelligence approach","volume":"2","author":"Michalski","year":"1986"},{"key":"S0269888900006366_ref056","doi-asserted-by":"publisher","DOI":"10.1145\/1968.1972"},{"key":"S0269888900006366_ref047","unstructured":"Quinlan JR , 1987. \u201cGenerating production rules from decision trees\u201d. 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