Fusion of Multiple Features and Supervised Learning for Chinese OOV Term Detection and POS Guessing
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1921-1925.
Abstract
In this paper, to support more precise Chinese Out-of-Vocabulary (OOV) term detection and Part-of-Speech (POS) guessing, a unified mechanism is proposed and formulated based on the fusion of multiple features and supervised learning. Besides all the traditional features, the new features for statistical information and global contexts are introduced, as well as some constraints and heuristic rules, which reveal the relationships among OOV term candidates. Our experiments on the Chinese corpora from both People’s Daily and SIGHAN 2005 have achieved the consistent results, which are better than those acquired by pure rule-based or statistics-based models. From the experimental results for combining our model with Chinese monolingual retrieval on the data sets of TREC-9, it is found that the obvious improvement for the retrieval performance can also be obtained.
@inproceedings{ijcai2011p321,
title = {Fusion of Multiple Features and Supervised Learning for Chinese OOV Term Detection and POS Guessing},
author = {Zhang, Yuejie and Cen, Lei and Wu, Wei and Jin, Cheng and Xue, Xiangyang},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {1921--1925},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-321},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-321},
}
TY - CPAPER TI - Fusion of Multiple Features and Supervised Learning for Chinese OOV Term Detection and POS Guessing AU - Zhang, Yuejie AU - Cen, Lei AU - Wu, Wei AU - Jin, Cheng AU - Xue, Xiangyang T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 1921 EP - 1925 DO - 10.5591/978-1-57735-516-8/IJCAI11-321 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-321 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: