Open AccessBook Chapter10.1007/978-3-540-30195-0_9

Learning Node Selecting Tree Transducer from Completely Annotated Examples

- 11 Oct 2004

- Vol. 3264, pp 91-102

TL;DR: This work introduces node selecting tree transducer (NSTT) and shows how to induce deterministic NSTTs in polynomial time from completely annotated examples.

Abstract: A base problem in Web information extraction is to find appropriate queries for informative nodes in trees. We propose to learn queries for nodes in trees automatically from examples. We introduce node selecting tree transducer (NSTT) and show how to induce deterministic NSTTs in polynomial time from completely annotated examples. We have implemented learning algorithms for NSTTs, started applying them to Web information extraction, and present first experimental results.

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1. What have the authors contributed in "Learning node selecting tree transducer from completely annotated examples" ?

The authors propose to learn queries for nodes in trees automatically from examples.. The authors introduce node selecting tree transducer ( NSTT ) and show how to induce deterministic NSTTs in polynomial time from completely annotated examples.. The authors have implemented learning algorithms for NSTTs, started applying them to Web information extraction, and present first experimental results.

2. What have the authors stated for future works in "Learning node selecting tree transducer from completely annotated examples" ?

In future work, the authors plan to continue improving their learning algorithms in practice.

Fig. 1. A simple Web page, its corresponding tree.

Fig. 5. Experimental results on Okra and Bigbook benchmarks. (∗ indicates results without and with the use of wild-cards).

Fig. 4. The inferred NSTT and its run on the example tree

Fig. 3. The initial automaton and its run on the example tree

Citations

•Proceedings Article

N-ary Queries by Tree Automata.

Joachim Niehren, +3 more

- 01 Jan 2005

TL;DR: It is shown that run-based n-ary queries capture MSO, contribute algorithms for enumerating answers of n-ARY queries, and study the complexity of the problem.

...read moreread less

153

•Proceedings Article

Inferring XML schema definitions from XML data

Geert Jan Bex, +2 more

- 23 Sep 2007

TL;DR: A theoretically complete algorithm is provided that always infers the correct XSD when a sufficiently large corpus of XML documents is available and a variant of this algorithm is presented that works well on real-world data sets.

...read moreread less

134

•Journal Article

Querying unranked trees with stepwise tree automata

Julien Carme, +2 more

- 01 Jan 2004

- Lecture Notes in Computer Science

TL;DR: Stepwise tree automata can express the same monadic queries as monadic Datalog and monadic second-order logic by reduction to the ranked case via a new systematic correspondence that relates unranked and ranked queries.

...read moreread less

•Journal Article•10.1007/S10994-006-9613-8

Interactive learning of node selecting tree transducer

Julien Carme, +3 more

- 01 Jan 2007

- Machine Learning

TL;DR: In this paper, the authors propose to represent monadic queries by bottom-up deterministic Node Selecting Tree Transducers (NSTTs), a particular class of tree automata that they introduce.

...read moreread less

•Proceedings Article

Interactive learning of node selecting tree transducer

Julien Carme, +3 more

- 01 Jan 2007

TL;DR: An interactive learning algorithm for monadic queries defined by pruning NSTTs is implemented, which satisfies a new formal active learning model in the style of Angluin (1987), and is integrated into a visually interactive Web information extraction system by plugging it into the Mozilla Web browser.

...read moreread less

...

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References

•Journal Article•10.1016/S0019-9958(67)91165-5

Language identification in the limit

E. Mark Gold

- 01 May 1967

- Information & Computation

TL;DR: It was found that theclass of context-sensitive languages is learnable from an informant, but that not even the class of regular languages is learningable from a text.

...read moreread less

3.8K

•Proceedings Article

Wrapper induction for information extraction

Nicholas Kushmerick, +1 more

- 01 Jan 1997

TL;DR: This work introduces wrapper induction, a method for automatically constructing wrappers, and identifies hlrt, a wrapper class that is e ciently learnable, yet expressive enough to handle 48% of a recently surveyed sample of Internet resources.

...read moreread less

1.2K

Journal Article•10.1007/BF01691346

Generalized finite automata theory with an application to a decision problem of second-order logic

James W. Thatcher, +1 more

- 01 Mar 1968

- Theory of Computing Systems \/ Mathemati...

TL;DR: The standard closure theorems are proved for the class of sets “recognizable” by finite algebras, and a generalization of Kleene's regularity theory is presented.

...read moreread less

841

Book•10.1007/3-540-44795-4

Machine Learning: ECML 2001

Luc De Raedt, +1 more

- 01 Jan 2001

TL;DR: This paper presents a missing link between Plotkin’s least general generalization formalism and generalization on the Order Sorted Feature (OSF) foundation and shows the correctness of the definition is given on the basis of the axiomatic foundation.

...read moreread less

192

Book•10.1007/978-3-662-08546-2

Mathematical System Theory

Athanasios C. Antoulas

- 01 Jan 1991

152

...

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Learning Node Selecting Tree Transducer from Completely Annotated Examples

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Most frequently asked questions

1. What have the authors contributed in "Learning node selecting tree transducer from completely annotated examples" ?

2. What have the authors stated for future works in "Learning node selecting tree transducer from completely annotated examples" ?

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Citations

N-ary Queries by Tree Automata.

Inferring XML schema definitions from XML data

Querying unranked trees with stepwise tree automata

Interactive learning of node selecting tree transducer

Interactive learning of node selecting tree transducer

References

Language identification in the limit

Wrapper induction for information extraction

Generalized finite automata theory with an application to a decision problem of second-order logic

Machine Learning: ECML 2001

Mathematical System Theory

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