Name
Abstract | ||
|---|---|---|
This paper presents a methodology for automatic learning of ontologies from Thai text corpora, by extraction of terms and
relations. A shallow parser is used to chunk texts on which we identify taxonomic relations with the help of cues: lexico-syntactic
patterns and item lists. The main advantage of the approach is that it simplify the task of concept and relation labeling
since cues help for identifying the ontological concept and hinting their relation. However, these techniques pose certain
problems, i.e. cue word ambiguity, item list identification, and numerous candidate terms. We also propose the methodology
to solve these problems by using lexicon and co-occurrence features and weighting them with information gain. The precision,
recall and F-measure of the system are 0.74, 0.78 and 0.76, respectively. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s10579-007-9045-5 | Language Resources and Evaluation |
Keywords | Field | DocType |
Thai ontology learning,Lexico-syntactic patterns,Taxonomic list | Ontology (information science),Ontology,Weighting,Computer science,Computational linguistics,Text corpus,Lexicon,Artificial intelligence,Natural language processing,Parsing,Ambiguity | Journal |
Volume | Issue | ISSN |
42 | 2 | 1574-020X |
Citations | PageRank | References |
9 | 0.60 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aurawan Imsombut | 1 | 9 | 0.60 |
| asanee kawtrakul | 2 | 161 | 25.90 |