Name
Abstract | ||
|---|---|---|
Traditional text information extraction methods mainly act on static documents and are difficult to reflect the dynamic evolvement of information update on the web. To address this challenge, this work proposes a new method based on shallow parsing with rules. The rules are generated according to the syntactic features of English texts, such as the tense of verbs, the usages of modal verbs and so on. The latest novel information in English news texts is extracted correctly, to meet the needs of users for accessing to updated information of the developing events quickly and effectively. Performance results show the improvement of the proposed scheme in this work. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/3PGCIC.2011.26 | 3PGCIC |
Keywords | Field | DocType |
shallow parsing,english text,performance result,traditional text information extraction,information update,web information extraction,updated information,update summarization,english news text,modal verb,new method,latest novel information,dynamic evolvement,internet,real time systems,data mining,text analysis,information retrieval,feature extraction,information extraction,natural language processing | Shallow parsing,Automatic summarization,Text mining,World Wide Web,Information retrieval,Computer science,Modal verb,Information extraction,Natural language processing,Artificial intelligence,Syntax,The Internet | Conference |
Citations | PageRank | References |
1 | 0.36 | 3 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Peng | 1 | 115 | 19.12 |
| Xiaoxiao Ma | 2 | 202 | 14.68 |
| Ye Tian | 3 | 1 | 0.36 |
| Ming Yang | 4 | 1 | 0.36 |
| Hua Long | 5 | 1 | 0.36 |
| Quanchen Lin | 6 | 1 | 0.36 |
| Xiaojun Xia | 7 | 6 | 1.20 |