Abstract: "In this paper, we introduce a new normal form for context-free grammars, called reversible context-free grammars, for the problem of learning context-free grammars from positive-only examples. A context-free grammar G = (N, [sigma], P, S) is said to be reversible if (1) A [is convert...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Sakakibara, Yasubumi (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Numazu, Japan 1989
Schriftenreihe:	International Institute for Advanced Study of Social Information Science <Numazu>: Research report 93
Schlagworte:	Computational linguistics Context (Linguistics)
Zusammenfassung:	Abstract: "In this paper, we introduce a new normal form for context-free grammars, called reversible context-free grammars, for the problem of learning context-free grammars from positive-only examples. A context-free grammar G = (N, [sigma], P, S) is said to be reversible if (1) A [is converted to] [alpha] and B [is converted to] [alpha] in P implies A = B and (2) A [is converted to] [alpha]B[beta] and A [is converted to] [alpha]C[beta] in P implies B = C. We show that the class of reversible context-free grammars is learnable from positive samples of structural descriptions and there exists an efficient algorithm to learn them from positive samples of structural descriptions, where a structural description of a context-free grammar is an unlabelled derivation tree of the grammar. This implies that if information on the structure of the grammar in the form of reversible is available to the learning algorithm, the full class of context-free languages can be learned efficiently from positive samples."
Beschreibung:	39 S.