Name
Abstract | ||
|---|---|---|
Aiming at the disadvantages of the word segmentation method based on string matching, the word segmentation method based on comprehension and the word segmentation method based on statistic, a novel field word segmentation model based on ontology was studied. With ontology technology introduced into Chinese word segmentation, the novel model eliminates ambiguities to a great extent and avoids semantic losing problem which is result from ignoring the context information in traditional Chinese word segmentation method. The experimental results show that the novel method can improve the segmentation precision greatly. And this study is valuable for next semantic retrieval in the future work. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CSCWD.2010.5471971 | CSCWD |
Keywords | Field | DocType |
chinese word segmentation,syntactic analysis,ambiguities,ontology,digital library,statistics,dictionaries,ontologies,information retrieval,frequency,semantics,natural languages,string matching,word segmentation,space technology,hidden markov models | Ontology (information science),String searching algorithm,Ontology,Scale-space segmentation,Information retrieval,Computer science,Segmentation,Segmentation-based object categorization,Text segmentation,Artificial intelligence,Natural language processing,Semantics | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4244-6763-1 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lizhen Liu | 1 | 38 | 7.95 |
| Chengli Wang | 2 | 1 | 0.96 |
| Lin Bai | 3 | 25 | 3.85 |
| Hai Chen | 4 | 13 | 4.14 |