Name
Title | ||
|---|---|---|
Automatic recognition of Chinese place names: a statistical and rule-based combined approach |
Abstract | ||
|---|---|---|
The automatic recognition of Chinese place names, a special case of the recognition of Chinese special nouns, is an important task in Chinese information processing. In this paper, we propose an approach combining statistical and rule-based techniques. The proposed approach discovers candidates from Chinese texts based upon the probability of a character being part of a Chinese place name; and confirms or eliminates the candidates by applying rules obtained by human summarization and transformation-based machine learning. In this approach, we employ a statistical measure: weight of likelihood (WOL), to estimate the likelihood of a character being part of a Chinese place name in real corpora. To the authors' knowledge, it is the first time WOL has been used to capture the capability of a character forming Chinese places names in real corpora. We evaluate the performance of our approach on a real data set and the recall and precision are 97% and 90.92% respectively |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ICSMC.2001.972883 | SMC |
Keywords | Field | DocType |
corpora,learning (artificial intelligence),human summarization,character recognition,chinese special nouns,transformation-based machine learning,weight of likelihood,chinese information processing,automatic chinese place name recognition,text analysis,rule-based techniques,statistical techniques,computer science,machine learning,information processing,learning artificial intelligence,information technology,dictionaries,noun,probability,rule based | Toponymy,Automatic summarization,Rule-based system,Information processing,Computer science,Information technology,Precision and recall,Noun,Natural language processing,Artificial intelligence,Machine learning,Special case | Conference |
Volume | Issue | ISSN |
4 | null | 1062-922X |
ISBN | Citations | PageRank |
0-7803-7087-2 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jia-heng Zheng | 1 | 9 | 4.17 |
| Hongye Tan | 2 | 25 | 6.11 |
| KaiYing Liu | 3 | 0 | 0.34 |
| Ying Zhao | 4 | 902 | 49.19 |