Using a more powerful teacher to reduce the number of queries of the l* algorithm in practical applications

Authors:
André L. Martins;H. Sofia Pinto;Arlindo L. Oliveira
Affiliations:
INESC-ID/IST, Lisboa, Portugal;INESC-ID/IST, Lisboa, Portugal;INESC-ID/IST, Lisboa, Portugal
Venue:
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Year:
2005

Citing 11
Cited 2

Learning regular sets from queries and counterexamples

Information and Computation
The design and analysis of efficient learning algorithms

The design and analysis of efficient learning algorithms
The minimum consistent DFA problem cannot be approximated within any polynomial

Journal of the ACM (JACM)
NoDoSE—a tool for semi-automatically extracting structured and semistructured data from text documents

SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Generating finite-state transducers for semi-structured data extraction from the Web

Information Systems - Special issue on semistructured data
Learning Information Extraction Rules for Semi-Structured and Free Text

Machine Learning - Special issue on natural language learning
Relational learning of pattern-match rules for information extraction

AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Extracting semi-structured data through examples

Proceedings of the eighth international conference on Information and knowledge management
A brief survey of web data extraction tools

ACM SIGMOD Record
Queries and Concept Learning

Machine Learning
Queries and Concept Learning

Machine Learning

USING GRAMMATICAL INFERENCE TECHNIQUES TO LEARN ONTOLOGIES THAT DESCRIBE THE STRUCTURE OF DOMAIN INSTANCES

Applied Artificial Intelligence
Inferring Finite-State Models with Temporal Constraints

ASE '08 Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work we propose to use a more powerful teacher to effectively apply query learning algorithms to identify regular languages in practical, real-world problems. More specifically, we define a more powerful set of replies to the membership queries posed by the L* algorithm that reduces the number of such queries by several orders of magnitude in a practical application. The basic idea is to avoid the needless repetition of membership queries in cases where the reply will be negative as long as a particular condition is met by the string in the membership query. We present an example of the application of this method to a real problem, that of inferring a grammar for the structure of technical articles.