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Ordered term tree languages which are polynomial time inductively inferable from positive data

2006
*
Theoretical Computer Science
*

We show that the class OTTL is

doi:10.1016/j.tcs.2005.10.022
fatcat:3n3rmwwjivcvddrpn2j7pk4bly
*polynomial**time**inductively**inferable**from**positive**data*, by giving a*polynomial**time*algorithm for solving the minimal*language*problem for OTTL . ... Given a set of*ordered**trees*S, the minimal*language*problem for OTTL = {L (t) | t ∈ OTT } is to find a linear*ordered**term**tree*t in OTT such that L (t) is minimal among all*term**tree**languages**which*... In [9, 15] , we gave some sets of unrooted unordered linear*term**trees*whose*languages**are**polynomial**time**inductively**inferable**from**positive**data*. ...##
###
Ordered Term Tree Languages which Are Polynomial Time Inductively Inferable from Positive Data
[chapter]

2002
*
Lecture Notes in Computer Science
*

In this paper, we consider a

doi:10.1007/3-540-36169-3_17
fatcat:plyiluerl5ggrpqh4yz6b3yoea
*polynomial**time*learnability of the class OTTL = {L(t) | t ∈ OTT }*from**positive**data*, where OTT denotes the set of all regular*ordered**term**trees*. ... For a regular*ordered**term**tree*t, the*term**tree**language*of t, denoted by L(t), is the set of all*trees**which**are*obtained*from*t by substituting arbitrary*trees*for all variables in t. ...*Polynomial**Time**Inductive**Inference*of*Ordered**Term**Tree**Languages**from**Positive**Data*We give the framework of*inductive**inference**from**positive**data*[3, 10] and show our main theorem. ...##
###
Polynomial Time Algorithms for Finding Unordered Tree Patterns with Internal Variables
[chapter]

2001
*
Lecture Notes in Computer Science
*

*inductively*

*inferable*

*from*

*positive*

*data*if the number of edge labels is infinite ... Finally, in

*order*to show that our

*polynomial*

*time*algorithm for the MINL problem can be applied to

*data*mining

*from*real-world Web documents, we show that regular

*term*

*tree*

*languages*

*are*

*polynomial*

*time*... We show that regular

*term*

*tree*

*languages*

*are*

*polynomial*

*time*

*inductively*

*inferable*

*from*

*positive*

*data*in Section 5. ...

##
###
Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables from Positive Data
[chapter]

2002
*
Lecture Notes in Computer Science
*

Then, by using these two algorithms, we show that the two classes of

doi:10.1007/3-540-45435-7_12
fatcat:offr2jaqfjhanec4mm3bkn2kei
*term**trees**are**polynomial**time**inductively**inferable**from**positive**data*. ... For a set of edge labels Λ and a*term**tree*t, the*term**tree**language*of t, denoted by LΛ(t), is the set of all labeled*trees**which**are*obtained*from*a*term**tree*t by substituting arbitrary labeled*trees*...*Polynomial**Time**Inductive**Inference*of*Ordered**Term**Tree**Languages**from**Positive**Data*We give the framework of*inductive**inference**from**positive**data*[3, 10] and show our main theorem. ...##
###
Polynomial Time Inductive Inference of TTSP Graph Languages from Positive Data

2009
*
IEICE transactions on information and systems
*

Finally, we show that L T T SP is

doi:10.1587/transinf.e92.d.181
fatcat:mzawe7zdabedjay3b5wjy3faxe
*polynomial**time**inductively**inferable**from**positive**data*. key words:*inductive**inference*, ... Firstly, when a TTSP graph G and a TTSP*term*graph g*are*given as inputs, we present a*polynomial**time*matching algorithm*which*decides whether or not L(g) contains G. ...*time**inductively**inferable**from**positive**data*. ...##
###
Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables
[chapter]

2003
*
Lecture Notes in Computer Science
*

These results imply that the classes of

doi:10.1007/978-3-540-39624-6_11
fatcat:wzrha3keqrczfhamqdutams4ge
*ordered*and unordered*term**trees**are**polynomial**time**inductively**inferable**from**positive**data*. ... Second, when Λ has more than one edge label, we give a*polynomial**time*algorithm for finding a minimally generalized*ordered**term**tree**which*explains all given*tree**data*. ... In [13, 14] , we showed that some fundamental classes of regular*ordered**term**tree**languages**are**polynomial**time**inductively**inferable**from**positive**data*. ...##
###
Finding minimal generalizations for unions of pattern languages and its application to inductive inference from positive data
[chapter]

1994
*
Lecture Notes in Computer Science
*

As results several classes of unions of pattern

doi:10.1007/3-540-57785-8_178
fatcat:nqbeqsqs5fap7ndi6ref4jnocu
*languages**are*shown to be*polynomial**time**inferable**from**positive**data*. ... In this paper we*are*concerning with*polynomial**time**inference**from**positive**data*of the class of unions of a bounded number of pattern*languages*. ... Since a minl of rst-*order**terms*can be uniquely determined as the least generalization in*polynomial**time*[Plo70] , the class of*tree*pattern*languages*is*polynomial**time**inferable**from**positive**data*. ...##
###
Learning of Finite Unions of Tree Patterns with Internal Structured Variables from Queries

2008
*
IEICE transactions on information and systems
*

Miyahara, •gOrdered

doi:10.1093/ietisy/e91-d.2.222
fatcat:6r2bja6ndvh6vfup3ifdhbqxbq
*term**tree**languages**which**are**polynomial**time**inductively**inferable**from**positive**data*,•h Theor. Comput. Sci., vol.350, pp. 63-90, 2006. ... Also our work [8], [15], [17] gave some classes of*languages*defined by extended*term**trees**which**are*poly- nomial*time**inductively**inferable**from**positive**data*. ...##
###
Learning of Finite Unions of Tree Patterns with Internal Structured Variables from Queries
[chapter]

2002
*
Lecture Notes in Computer Science
*

The

doi:10.1007/3-540-36187-1_46
fatcat:lucm5s6o6faz5eopuuj7u6qcxi
*language*L(t) of a*term**tree*t is the set of all*trees**which**are*obtained*from*t by substituting arbitrary*trees*for all variables in t. ... We show that any finite union of*languages*defined by m*term**trees*is exactly identifiable in*polynomial**time*using at most 2mn 2 restricted subset queries and at most m + 1 equivalence queries, where ... Also our work [14] showed the class OT T 1, * Λ is*polynomial**time**inductively**inferable**from**positive**data*. ...##
###
Page 2879 of Mathematical Reviews Vol. , Issue 2003d
[page]

2003
*
Mathematical Reviews
*

Summary: “This paper studies the

*polynomial*-*time*learnability of the classes of*ordered*gapped*tree*patterns (OGT) and*ordered*gapped forests (OGF) under the into-matching semantics in the query learning ... The question of*inferring*them*from*infinite examples has already been studied, but it may seem more reasonable to believe that the*data**from**which*we want to learn is a set of finite words, namely the ...##
###
Page 3353 of Mathematical Reviews Vol. , Issue 2001E
[page]

2001
*
Mathematical Reviews
*

In this paper we consider the

*inductive**inference*of unbounded unions of pattern*languages**from**positive**data*. ... YUT-AI; Iizuka); Arimura, Hiroki (J-K YUS-IF; Fukuoka)*Inductive**inference*of unbounded unions of pattern*languages**from**positive**data*. ...##
###
A bibliographical study of grammatical inference

2005
*
Pattern Recognition
*

The field of grammatical

doi:10.1016/j.patcog.2005.01.003
fatcat:62qwskiqcvddjobakbdshwebqq
*inference*(also known as grammar*induction*) is transversal to a number of research areas including machine learning, formal*language*theory, syntactic and structural pattern recognition ... Some of these papers*are*essential and should constitute a common background to research in the area, whereas others*are*specialized on particular problems or techniques, but can be of great help on specific ... settings (see Section 2.4); and for those learning paradigms in*which*DFA learning is possible, such as active learning or learning*from**polynomial**time*and*data*(see Section 2.2), the*positive*results ...##
###
Grammatical Inference in Software Engineering: An Overview of the State of the Art
[chapter]

2013
*
Lecture Notes in Computer Science
*

Software engineering can also benefit

doi:10.1007/978-3-642-36089-3_12
fatcat:3qp3xzhhqjgwdhguesrjnvotra
*from*grammatical*inference*. ... Grammatical*inference*-used successfully in a variety of fields such as pattern recognition, computational biology and natural*language*processing -is the process of automatically*inferring*a grammar by ... Anecdotally, it appears a fruitful method to find*polynomial*-*time*learning algorithms for context-free*languages**from**positive*samples is to adapt corresponding algorithms*from*DFA*inference*, with the ...##
###
Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data
[chapter]

2003
*
Lecture Notes in Computer Science
*

Finally we conclude that the class OTT c is

doi:10.1007/978-3-540-39917-9_23
fatcat:bew7ts5k4net7jdwnugybtsgxa
*polynomial**time**inductively**inferable**from**positive**data*. ... For a*term**tree*t in OTT c , the*term**tree**language*L(t) of t is the set of all unlabeled*ordered**trees**which**are*obtained*from*t by replacing all variables with unlabeled*ordered**trees*. ... In [5, 8, 9] , we showed that some classes of regular unordered*term**tree**languages**are**polynomial**time**inductively**inferable**from**positive**data*. ...##
###
Recent advances of grammatical inference

1997
*
Theoretical Computer Science
*

Sakakibarai Theoretical Computer Science 185 (1997) 1545 I') unknown DFA A made by an

doi:10.1016/s0304-3975(97)00014-5
fatcat:4a4minst2nerti32iagjxf25ty
*inference*algorithm: membership query and equivalence query. ... In this paper, we provide a survey of recent advances in the field "Grammatical*Inference*" with a particular emphasis on the results concerning the learnability of target classes represented by deterministic ... Kyushu Institute of Technology), Takeshi Koshiba, Masahiro Matsuoka, Yuji Takada, and Takashi Yokomori (currently, at University of Electro-Communications) for their excellent contributions to grammatical*inference*...
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