文法推断：算法与应用 Grammatical inference
分類: 图书,计算机/网络,计算机理论,
作者： Pieter Adriaans著
出 版 社： 湖南文艺出版社
出版时间： 2002-12-1字数：版次： 1页数： 314印刷时间： 2002/12/01开本：印次：纸张： 胶版纸I S B N ： 9783540442394包装： 平装编辑推荐
LNBI is devoted to the publication of state-of-the-art research results in bio-informatics and computational biology, at a high level and in both printed and electronic versions - making use of the well-established LNCS publication machinery. As with the LNCS mother series, refereed proceedings and post- proceedings are at the core of LNBI, however, similar to the color cover sub- lines in LNCS, tutorials and state-of-the-art surveys are also invited for LNBI. Among the topics covered are：
Genomics；Molecular sequence analysis；Recognition of genes and regulatory elements；Molecular evolution；Protein structure；Gene expression；Gene networks；Combinatorial libraries and drug design；Computational proteomics.
内容简介
This book constitutes the refereed proceedings of the 6th International Colloquium on Grammatical Inference, ICGI 2002, held in Amsterdam, The Netherlands in September 2002.The 28 revised full papers presented together with 7 software descriptions were carefully reviewed and selected from 48 submissions. The papers address issues in machine learning, automata, theoretical computer science, computational linguistics, and grammar systems as well as applications in fields like natural language processing, pattern recognition, computational biology, information retrieval, text processing, and data compression.
目录
Contributions
Inference of Sequential Association Rules Guided by Context-FreeGrammars
PCFG Learning by Nonterminal Partition Search
Inferring Subclasses of Regular Languages Faster Using RPNI andForbidden Configurations
Beyond EDSM
Consistent Identification in the Limit of Rigid Grammars from StringsIs NP-hard
Some Classes of Regular Languages Identifiable in the Limit fromPositive Data
Learning Probabilistic Residual Finite State Automata
Fragmentation: Enhancing Identifiability
On Limit Points for Some Variants of Rigid Lambek Grammars
Generalized Stochastic Tree Automata for Multi-relational Data Mining
On Sufficient Conditions to Identify Classes of Grammars fromPolynomial Time and Data
Stochastic Grammatical Inference with Multinomial Tests
Learning Languages with Help
Incremental Learning of Context Free Grammars
Estimating Grammar Parameters Using Bounded Memory
Stochastic k-testable Tree Languages and Applications
Fast Learning from Strings of 2-Letter Rigid Grammars
Learning Locally Testable Even Linear Languages from Positive Data
Inferring Attribute Grammars with Structured Data for NaturalLanguage Processing
A PAC Learnability of Simple Deterministic Languages
On the Learnability of Hidden Markov Models
Shallow Parsing Using Probabilistic Grammatical Inference
Learning of Regular Bi-w Languages
Software Descriptions
The EMILE 4.1 Grammar Induction Toolbox
Software for Analysing Recurrent Neural Nets That Learn to PredictNon-regular Languages
A Framework for Inductive Learning of Typed-Unification Grammars
A Tool for Language Learning Based on Categorial Grammars andSemantic Information
‘NAIL’: Artificial Intelligence Software for Learning Natural Language
……
Autor Index
