Summary of the paper
| Title | Automatic Grammar Rule Extraction and Ranking for Definitions |
|---|---|
| Authors | Claudia Borg, Mike Rosner and Gordon J. Pace |
| Abstract | Plain text corpora contain much information which can only be accessed throughhuman annotation and semantic analysis, which is typically very time consumingto perform. Analysis of such texts at a syntactic or grammatical structurelevel can however extract some of this information in an automated manner, evenif identifying effective rules can be extremely difficult. One such type ofimplicit information present in texts is that of definitional phrases andsentences. In this paper, we investigate the use of evolutionary algorithms tolearn classifiers to discriminate between definitional and non-definitionalsentences in non-technical texts, and show how effective grammar-baseddefinition discriminators can be automatically learnt with minor humanintervention. |
| Language | Text mining |
| Topics | Information Extraction, Information Retrieval, Statistical and machine learning methods, Text mining |
Full paper  |
Automatic Grammar Rule Extraction and Ranking for Definitions |
| Bibtex | @InProceedings{BORG10.609, author = {Claudia Borg, Mike Rosner and Gordon J. Pace}, title = {Automatic Grammar Rule Extraction and Ranking for Definitions}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |