An Associative Concept Dictionary for Verbs and its Application to Elliptical Word Estimation

Takehiro Teraoka, Jun Okamoto, Shun Ishizaki


Abstract
Natural language processing technology has developed remarkably, but it is still difficult for computers to understand contextual meanings as humans do. The purpose of our work has been to construct an associative concept dictionary for Japanese verbs and make computers understand contextual meanings with a high degree of accuracy. We constructed an automatic system that can be used to estimate elliptical words. We present the result of comparing words that were estimated both by our proposed system (VNACD) and three baseline systems (VACD, NACD, and CF). We then calculated the mean reciprocal rank (MRR), top N accuracy (top 1, top 5, and top 10), and the mean average precision (MAP). Finally, we showed the effectiveness of our method for which both an associative concept dictionary for verbs (Verb-ACD) and one for nouns (Noun-ACD) were used. From the results, we conclude that both the Verb-ACD and the Noun-ACD play a key role in estimating elliptical words.
Anthology ID:
L10-1120
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/181_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Takehiro Teraoka, Jun Okamoto, and Shun Ishizaki. 2010. An Associative Concept Dictionary for Verbs and its Application to Elliptical Word Estimation. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
An Associative Concept Dictionary for Verbs and its Application to Elliptical Word Estimation (Teraoka et al., LREC 2010)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/181_Paper.pdf