Summary of the paper
| Title | A Statistical Method for Detecting the Arabic Empty Category |
|---|---|
| Authors | Hitham M. Abo Bakr, Khaled Shaalan and Ibrahim Ziedan |
| Abstract | In this paper we introduce a statistical approach for detecting the position of Empty-Category presented in Arabic Treebank that can help for detecting the position of the elliptic personnel pronoun and some free word order detection. The approach requires a large corpus of text. We made the training for detecting the Empty-Category for each token based on its Part Of Speech (POS) and BP-chunk position as well as the position of token in the statement. The Empty-Category detection is then efficiently obtained using the SVM technique. We presented an evaluation of the proposed diacritization algorithm and discussed various modifications for improving the performance of this approach. |
| Topics | Extraction and acquisition of knowledge (e.g. terms, lexical information, language modelling) from LRs, Methods, tools and procedures for acquisition, creation, management, access, distribution and use of Arabic LRs |
Full paper  |
A Statistical Method for Detecting the Arabic Empty Category |
| Bibtex | @InProceedings{MABOBAKR09.32, author = {Hitham M. Abo Bakr, Khaled Shaalan and Ibrahim Ziedan}, title = {A Statistical Method for Detecting the Arabic Empty Category}, booktitle = {Proceedings of the Second International Conference on Arabic Language Resources and Tools}, year = {2009}, month = {April}, date = {22-23}, address = {Cairo, Egypt}, editor = {Khalid Choukri and Bente Maegaard}, publisher = {The MEDAR Consortium}, isbn = {2-9517408-5-9}, language = {english} } |