Grammatical Inference Algorithms and Applications

Grammatical Inference  Algorithms and Applications

The Fifth International Colloquium on Grammatical Inference (ICGI-2000) was held in Lisbon on September 11–13th, 2000. ICGI-2000 was the fifth in a series of successful biennial international conferences in the area of grammatical ...

Author: Arlindo L. Oliveira

Publisher: Springer

ISBN: 9783540452577

Category: Computers

Page: 316

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This book constitutes the refereed proceedings of the 5th International Colloquium on Grammatical Inference, ICGI 2000, held in Lisbon, Portugal in September 2000. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers address topics like machine learning, automata, theoretical computer science, computational linguistics, pattern recognition, artificial neural networks, natural language acquisition, computational biology, information retrieval, text processing, and adaptive intelligent agents.
Categories: Computers

Grammatical Inference Algorithms and Applications

Grammatical Inference  Algorithms and Applications

It trans- js natural language sentences by mapping grammar rules (which are uced by the Alignment-Based Learning grammatical inference frame- i) of the source language to those of the target language. By parsing entence in the source ...

Author: Yasibumi Sakaibara

Publisher: Springer Science & Business Media

ISBN: 9783540452645

Category: Computers

Page: 359

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This book constitutes the refereed proceedings of the 8th International Colloquium on Grammatical Inference, ICGI 2006. The book presents 25 revised full papers and 8 revised short papers together with 2 invited contributions, carefully reviewed and selected. The topics discussed range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to applications to natural language processing.
Categories: Computers

Grammatical Inference

Grammatical Inference

A survey of results in grammatical inference . In S. Watanabe , editor , Frontiers of Pattern Recognition , Academic Press , pages 31-54 , 1972 . ( CM96 ] D. Carmel and S. Markovitch . Learning models of intelligent agents .

Author: Vasant Honavar

Publisher: Springer Science & Business Media

ISBN: 3540647767

Category: Computers

Page: 270

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This book constitutes the refereed proceedings of the Fourth International Colloquium on Grammatical Inference, ICGI-98, held in Ames, Iowa, in July 1998. The 23 revised full papers were carefully reviewed and selected for inclusion in the book from a total of 35 submissions. The book addresses a wide range of grammatical inference theory such as automata induction, grammar induction, automatic language acquisition, etc. as well as a variety of applications in areas like syntactic pattern recognition, adaptive intelligent agents, diagnosis, computational biology, data mining, and knowledge discovery.
Categories: Computers

Grammatical Inference

Grammatical Inference

Grammatical Inference: Algorithms and Applications, Proceedings ofICGI '02, volume 2484 of LNAI. Springer-Verlag, 2002. P. Adriaans and C. Jacobs. Using MDL for grammar induction. In Sakakibara et al. (2006), pages 293–307.

Author: Colin de la Higuera

Publisher: Cambridge University Press

ISBN: 9781139486682

Category: Computers

Page:

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The problem of inducing, learning or inferring grammars has been studied for decades, but only in recent years has grammatical inference emerged as an independent field with connections to many scientific disciplines, including bio-informatics, computational linguistics and pattern recognition. This book meets the need for a comprehensive and unified summary of the basic techniques and results, suitable for researchers working in these various areas. In Part I, the objects of use for grammatical inference are studied in detail: strings and their topology, automata and grammars, whether probabilistic or not. Part II carefully explores the main questions in the field: What does learning mean? How can we associate complexity theory with learning? In Part III the author describes a number of techniques and algorithms that allow us to learn from text, from an informant, or through interaction with the environment. These concern automata, grammars, rewriting systems, pattern languages or transducers.
Categories: Computers

Grammatical Inference for Computational Linguistics

Grammatical Inference for Computational Linguistics

This is formal grammatical inference. On the other hand, however, in the absence of such results that can be immediately deployed for everyday useful tasks, empirical grammatical inference develops learning systems that aim to be ...

Author: Jeffrey Heinz

Publisher: Springer Nature

ISBN: 9783031021596

Category: Computers

Page: 139

View: 853

This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols. The relationship to computational linguistics is natural because many research problems in computational linguistics are learning problems on words, phrases, and sentences: What algorithm can take as input some finite amount of data (for instance a corpus, annotated or otherwise) and output a system that behaves "correctly" on specific tasks? Throughout the text, the key concepts of grammatical inference are interleaved with illustrative examples drawn from problems in computational linguistics. Special attention is paid to the notion of "learning bias." In the context of computational linguistics, such bias can be thought to reflect common (ideally universal) properties of natural languages. This bias can be incorporated either by identifying a learnable class of languages which contains the language to be learned or by using particular strategies for optimizing parameter values. Examples are drawn largely from two linguistic domains (phonology and syntax) which span major regions of the Chomsky Hierarchy (from regular to context-sensitive classes). The conclusion summarizes the major lessons and open questions that grammatical inference brings to computational linguistics. Table of Contents: List of Figures / List of Tables / Preface / Studying Learning / Formal Learning / Learning Regular Languages / Learning Non-Regular Languages / Lessons Learned and Open Problems / Bibliography / Author Biographies
Categories: Computers

Grammatical Inference Algorithms and Applications

Grammatical Inference  Algorithms and Applications

This paper describes the Omphalos Context-Free Grammar Learning Competition held as part of the International Colloquium on Grammatical Inference 2004. The competition was created in an effort to promote the development of new and ...

Author: Georgios Paliouras

Publisher: Springer

ISBN: 9783540301950

Category: Computers

Page: 296

View: 457

Categories: Computers

Grammatical Inference Algorithms and Applications

Grammatical Inference  Algorithms and Applications

Problems with Evaluation of Unsupervised Empirical Grammatical Inference Systems Menno van Zaanen and Jeroen Geertzen Dept. of Communication & Information Sciences Tilburg University Tilburg, The Netherlands {mvzaanen ...

Author: Alexander Clark

Publisher: Springer

ISBN: 9783540880097

Category: Computers

Page: 305

View: 172

This book constitutes the refereed proceedings of the 9th International Colloquium on Grammatical Inference, ICGI 2008, held in Saint-Malo, France, in September 2008. The 21 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 36 submissions. The topics of the papers presented vary from theoretical results of learning algorithms to innovative applications of grammatical inference, and from learning several interesting classes of formal grammars to applications to natural language processing.
Categories: Computers

State of the Art on Grammatical Inference Using Evolutionary Method

State of the Art on Grammatical Inference Using Evolutionary Method

In: Honavar, V., Slutski, G. (Eds.), Grammatical Inference, Proceedings of ICGI '98, Lecture Notes in Artificial Intelligence, vol. 1433. Springer, Berlin, Heidelberg, pp. 257e270. Boström, 1998. Predicate invention and learning from ...

Author: Hari Mohan Pandey

Publisher: Academic Press

ISBN: 9780128221549

Category: Science

Page: 228

View: 990

State of the Art on Grammatical Inference Using Evolutionary Method presents an approach for grammatical inference (GI) using evolutionary algorithms. Grammatical inference deals with the standard learning procedure to acquire grammars based on evidence about the language. It has been extensively studied due to its high importance in various fields of engineering and science. The book's prime purpose is to enhance the current state-of-the-art of grammatical inference methods and present new evolutionary algorithms-based approaches for context free grammar induction. The book's focus lies in the development of robust genetic algorithms for context free grammar induction. The new algorithms discussed in this book incorporate Boolean-based operators during offspring generation within the execution of the genetic algorithm. Hence, the user has no limitation on utilizing the evolutionary methods for grammatical inference. Discusses and summarizes the latest developments in Grammatical Inference, with a focus on Evolutionary Methods Provides an understanding of premature convergence as well as genetic algorithms Presents a performance analysis of genetic algorithms as well as a complete look into the wide range of applications of Grammatical Inference methods Demonstrates how to develop a robust experimental environment to conduct experiments using evolutionary methods and algorithms
Categories: Science

Grammatical Inference Theoretical Results and Applications

Grammatical Inference  Theoretical Results and Applications

Dupont, P.: Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method. In: Carrasco, R.C., Oncina, J. (eds.) ICGI 1994. LNCS, vol. 862, pp. 236–245. Springer, Heidelberg (1994) 6.

Author: José Sempere

Publisher: Springer

ISBN: 9783642154881

Category: Computers

Page: 317

View: 254

Annotation This book constitutes the refereed proceedings of the 10th International Colloquium on Grammatical Inference, ICGI 2010, held in Valencia, Spain, in September 2010. The 18 revised full papers and 14 revised short papers presented were carefully reviewed and selected from numerous submissions. The topics of the papers presented vary from theoretical results about the learning of different formal language classes (regular, context-free, context-sensitive, etc.) to application papers on bioinformatics, language modelling or software engineering. Furthermore there are two invited papers on the topics grammatical inference and games and molecules, languages, and automata.
Categories: Computers

Grammatical Inference Algorithms and Applications

Grammatical Inference  Algorithms and Applications

Juillé, H. and Pollack J. A Stochastic Search Approach to Grammar Induction. In Grammatical Inference. V. Honavar and G. Slutzki (Eds.) LNAI 1433. SpringerVerlag, pp 126-137 (1998). Lang , K.J. Random DFA's can be Approximately Learned ...

Author: Pieter Adriaans

Publisher: Springer

ISBN: 9783540457909

Category: Computers

Page: 318

View: 173

The Sixth International Colloquium on Grammatical Inference (ICGI2002) was held in Amsterdam on September 23-25th, 2002. ICGI2002 was the sixth in a series of successful biennial international conferenceson the area of grammatical inference. Previous meetings were held in Essex, U.K.; Alicante, Spain; Mo- pellier, France; Ames, Iowa, USA; Lisbon, Portugal. This series of meetings seeks to provide a forum for the presentation and discussion of original research on all aspects of grammatical inference. Gr- matical inference, the process of inferring grammars from given data, is a ?eld that not only is challenging from a purely scienti?c standpoint but also ?nds many applications in real-world problems. Despite the fact that grammatical inference addresses problems in a re- tively narrow area, it uses techniques from many domains, and is positioned at the intersection of a number of di?erent disciplines. Researchers in grammatical inference come from ?elds as diverse as machine learning, theoretical computer science, computational linguistics, pattern recognition, and arti?cial neural n- works. From a practical standpoint, applications in areas like natural language - quisition, computational biology, structural pattern recognition, information - trieval, text processing, data compression and adaptive intelligent agents have either been demonstrated or proposed in the literature. The technical program included the presentation of 23 accepted papers (out of 41 submitted). Moreover, for the ?rst time a software presentation was or- nized at ICGI. Short descriptions of the corresponding software are included in these proceedings, too.
Categories: Computers