<P>This book constitutes the refereed proceedings of the 7th International Colloquium on Grammatical Inference, ICGI 2004, held in Athens, Greece in October 2004.</P><P>The 20 revised full papers and 8 revised poster papers presented together with 3 invited contributions were carefully reviewed and
Grammatical Inference: Algorithms and Applications: 7th International Colloquium, ICGI 2004, Athens, Greece, October 11-13, 2004. Proceedings (Lecture Notes in Computer Science, 3264)
β Scribed by Georgios Paliouras (editor), Yasubumi Sakakibara (editor)
- Publisher
- Springer
- Year
- 2004
- Tongue
- English
- Leaves
- 309
- Edition
- 2004
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The 7th International Colloquium on Grammatical Inference (ICGI 2004) was heldintheNationalCentreforScienti?cResearch"Demokritos", Athens, Greece on October 11-13, 2004. ICGI 2004 was the seventh in a series of successful biennial international conferences in the area of grammaticalinference. Previous meetings were held in Essex, UK; Alicante, Spain; Montpellier, France; Ames, Iowa, USA; Lisbon, Portugal; and Amsterdam, The Netherlands. This series of conferences seeks to provide a forum for the presentation and discussion of original research papers on all aspects of grammatical inference. Grammatical inference, the study of learning grammars from data, is an - tablishedresearch?eldinarti?cialintelligence, datingbacktothe1960s, andhas been extensively addressed by researchers in automata theory, language acqui- tion, computational linguistics, machine learning, pattern recognition, compu- tional learning theory and neural networks. ICGI 2004 emphasized the multid- ciplinary natureoftheresearch?eldandthe diversedomains inwhich gramm- ical inference is being applied, such as natural language acquisition, compu- tionalbiology, structuralpatternrecognition, informationretrieval, Webmining, text processing, data compression and adaptive intelligent agents. We received 45 high-quality papers from 19 countries. The papers were - viewed by at least two - in most cases three - reviewers. In addition to the 20 full papers, 8 short papers that received positive comments from the reviewers were accepted, and they appear in a separate section of this volume. The t- ics of the accepted papers vary from theoretical results of learning algorithms to innovative applications of grammatical inference, and from learning several interesting classes of formal grammars to estimations of probabilistic grammars.
β¦ Table of Contents
3540234101
Table of Contents
Invited Papers
Learning and Mathematics
Learning Finite-State Models for Machine Translation
The Omphalos Context-Free Grammar Learning Competition
Regular Papers
Mutually Compatible and Incompatible Merges for the Search of the Smallest Consistent DFA
Faster Gradient Descent Training of Hidden Markov Models, Using Individual Learning Rate Adaptation
Learning Mild Context-Sensitiveness: Toward Understanding Childrenβs Language Learning
Learnability of Pregroup Grammars
A Markovian Approach to the Induction of Regular String Distributions
Learning Node Selecting Tree Transducer from Completely Annotated Examples
Identifying Clusters from Positive Data
Introducing Domain and Typing Bias in Automata Inference
Analogical Equations in Sequences: Definition and Resolution
Representing Languages by Learnable Rewriting Systems
A Divide-and-Conquer Approach to Acquire Syntactic Categories
Grammatical Inference Using Suffix Trees
Learning Stochastic Finite Automata
Navigation Pattern Discovery Using Grammatical Inference
A Corpus-Driven Context-Free Approximation of Head-Driven Phrase Structure Grammar
Partial Learning Using Link Grammars Data
eg-GRIDS: Context-Free Grammatical Inference from Positive Examples Using Genetic Search
The Boisdale Algorithm β An Induction Method for a Subclass of Unification Grammar from Positive Data
Learning Stochastic Deterministic Regular Languages
Polynomial Time Identification of Strict Deterministic Restricted One-Counter Automata in Some Class from Positive Data
Poster Papers
Learning Syntax from Function Words
Running FCRPNI in Efficient Time for Piecewise and Right Piecewise Testable Languages
Extracting Minimum Length Document Type Definitions Is NP-Hard
Learning Distinguishable Linear Grammars from Positive Data
Extending Incremental Learning of Context Free Grammars in Synapse
Identifying Left-Right Deterministic Linear Languages
Efficient Learning of k-Reversible Context-Free Grammars from Positive Structural Examples
An Analysis of Examples and a Search Space for PAC Learning of Simple Deterministic Languages with Membership Queries
Author Index
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