Graph mutual reinforcement based bootstrapping

Authors:
Qi Zhang;Yaqian Zhou;Xuanjing Huang;Lide Wu
Affiliations:
Department of Computer Science and Engineering, Fudan University;Department of Computer Science and Engineering, Fudan University;Department of Computer Science and Engineering, Fudan University;Department of Computer Science and Engineering, Fudan University
Venue:
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Year:
2008

Citing 14
Cited 1

Elements of information theory

Elements of information theory
Combining labeled and unlabeled data with co-training

COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Authoritative sources in a hyperlinked environment

Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Learning dictionaries for information extraction by multi-level bootstrapping

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
Snowball: extracting relations from large plain-text collections

DL '00 Proceedings of the fifth ACM conference on Digital libraries
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Deep Read: a reading comprehension system

ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A graph model for unsupervised lexical acquisition

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
A bootstrapping method for learning semantic lexicons using extraction pattern contexts

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning subjective nouns using extraction pattern bootstrapping

CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Unsupervised information extraction approach using graph mutual reinforcement

EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Hierarchical hidden Markov models for information extraction

IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Unsupervised named-entity extraction from the Web: An experimental study

Artificial Intelligence
Automatically generating extraction patterns from untagged text

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2

Cause identification from aviation safety incident reports via weakly supervised semantic lexicon construction

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a new bootstrapping method based on Graph Mutual Reinforcement (GMR-Bootstrapping) to learn semantic lexicons. The novelties of this work include 1) We integrate Graph Mutual Reinforcement method with the Bootstrapping structure to sort the candidate words and patterns; 2) Pattern's uncertainty is defined and used to enhance GMR-Bootstrapping to learn multiple categories simultaneously. Experimental results on MUC4 corpus show that GMR-Bootstrapping outperforms the state-of-the-art algorithms. We also use it to extract names of automobile manufactures and models from Chinese corpus. It achieves good results too.