Summary of the paper
| Title | AutoTagTCG : A Framework for Automatic Thai CG Tagging |
|---|---|
| Authors | Thepchai Supnithi, Taneth Ruangrajitpakorn, Kanokorn Trakultaweekool and Peerachet Porkaew |
| Abstract | This paper aims to develop a framework for automatic CG tagging. Weinvestigated two main algorithms, CRF and Statistical alignment model based oninformation theory (SAM). We found that SAM gives the best results both inword level and sentence level. We got the accuracy 89.25% in word level and82.49% in sentence level. Combining both methods can be suited for both knownand unknown word. |
| Language | |
| Topics | LR Infrastructures and Architectures, Tools, systems, applications |
Full paper  |
AutoTagTCG : A Framework for Automatic Thai CG Tagging |
| Bibtex | @InProceedings{SUPNITHI10.868, author = {Thepchai Supnithi, Taneth Ruangrajitpakorn, Kanokorn Trakultaweekool and Peerachet Porkaew}, title = {AutoTagTCG : A Framework for Automatic Thai CG Tagging}, 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} } |