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

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.