Name
Abstract | ||
|---|---|---|
This paper presents a new model for automatic acquisition of lexical concepts from text, referred to as Concept Inner-Constructive Model (CICM). The CICM clarifies the rules when words construct concepts through four aspects including (1) parts of speech, (2) syllable, (3) senses and (4) attributes. Firstly, we extract a large number of candidate concepts using lexico-patterns and confirm a part of them to be concepts if they matched enough patterns for some times. Then we learn CICMs using the confirmed concepts automatically and distinguish more concepts with the model. Essentially, the CICM is an instances learning model but it differs from most existing models in that it takes into account a variety of linguistic features and statistical features of words as well. And for more effective analogy when learning new concepts using CICMs, we cluster similar words based on density. The effectiveness of our method has been evaluated on a 160G raw corpus and 5,344,982 concepts are extracted with a precision of 89.11% and a recall of 84.23%. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76719-0_27 | KSEM |
Keywords | Field | DocType |
automatic acquisition,candidate concept,cluster similar word,effective analogy,new model,large number,enough pattern,existing model,concept inner-constructive model,new concept,inner-constructive model,part of speech,knowledge discovery,text mining | Constructive,Computer science,Part of speech,Natural language processing,Artificial intelligence,Knowledge extraction,Syllable,Analogy,Recall,Machine learning | Conference |
Volume | ISSN | ISBN |
4798.0 | 0302-9743 | 3-540-76718-5 |
Citations | PageRank | References |
7 | 0.64 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shi Wang | 1 | 28 | 12.46 |
| Ya-nan Cao | 2 | 131 | 19.42 |
| Xinyu Cao | 3 | 18 | 1.94 |
| Cungen Cao | 4 | 309 | 58.63 |