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The Generality Of Overgenerality  (Make Corrections)  (14 citations)
William W. Cohen
Machine Learning



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Abstract: Theory specialization is the process of using examples to specialize an overgeneral domain theory. This paper shows by example that many different types of background knowledge can be encoded as overgeneral theories, and further, that these theories can be specialized using existing theory specialization techniques. A consequence of this is that theory specialization techniques are a surprisingly general way of making use of background knowledge. 1 INTRODUCTION Several recent papers ... (Update)

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.... and used extensively for top down induction of logic programs (e.g. in mis [ Shapiro,1983 ] foil [ Quinlan,1990 ] ana ebl [ Cohen,1991 ] focl [ Pazzani et al.,1991 ] grendel [ Cohen,1992 ] and focl frontier [ Pazzani and Brunk,1993 ] This work contributes to...

.... programming, the top down search for an inductive hypothesis has been performed by using various specialization techniques [14, 2, 8, 12, 10, 3, 7, 13, 16, 9]. In this work, we assume that the overly general hypothesis is given as a logic program. The problem of finding an...

Cited by:   More
Grammatically Biased Learning: Learning Horn Theories Using an.. - Cohen (1991)   (Correct)
Theory-Guided Induction of Logic Programs by Inference of Regular .. - Boström (1996)   (Correct)
Extraction and Use of Contextual Attributes for Theory.. - Andrea Pohoreckyj.. (1992)   (Correct)

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0.3:   Towards a Theory of Strong Overgeneral Classifiers - Kovacs (2000)   (Correct)
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11:   Learning Logical Definitions from Relations (context) - Quinlan - 1990
9:   Algorithmic Program Debugging (context) - Shapiro - 1983
9:   Compiling Prior Knowledge into an Explicit Bias - Cohen - 1992

BibTeX entry:   (Update)

Cohen, W. (1991a). The generality of overgenerality. http://citeseer.ist.psu.edu/403963.html   More

@inproceedings{ cohen91generality,
    author = "William W. Cohen",
    title = "The Generality of Overgenerality",
    booktitle = "Machine Learning",
    pages = "490-494",
    year = "1991",
    url = "citeseer.ist.psu.edu/403963.html" }
Citations (may not include all citations):
149   Quantifying inductive bias: AI learning algorithms and Valia.. (context) - Haussler - 1988  ACM   DBLP
24   Learning from textbook knowledge: A case study - Cohen - 1990  DBLP
21   Induction in abstraction spaces: A form of constructive indu.. (context) - Drastal, Czako et al. - 1989
5   Using determinations in EBL: A solution to the incomplete th.. (context) - Mahadevan - 1989  ACM   DBLP
4   A decision tree approach to theory specialization (context) - Cohen - 1991
2   Induction over the unexplained (context) - Mooney, Ourston - 1989
2   Creating a Memory of Causal Relationships (context) - Pazzani - 1990  ACM
1   Explanation-based learning with weak domain theories (context) - Pazzani - 1989  ACM



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Documents on the same site (http://www.research.whizbang.com/~wcohen/):   More
An Analysis of Representation Shift In Concept Learning - Cohen (1990)   (Correct)
Learnability of the CLASSIC Knowledge Representation Language - Cohen, Hirsh (1993)   (Correct)
Learning Approximate Control Rules Of High Utility - Cohen (1990)   (Correct)

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