tailieunhanh - Báo cáo khoa học: "Combining Lexical Semantic Resources with Question & Answer Archives for Translation-Based Answer Finding"

Monolingual translation probabilities have recently been introduced in retrieval models to solve the lexical gap problem. They can be obtained by training statistical translation models on parallel monolingual corpora, such as question-answer pairs, where answers act as the “source” language and questions as the “target” language. In this paper, we propose to use as a parallel training dataset the definitions and glosses provided for the same term by different lexical semantic resources. We compare monolingual translation models built from lexical semantic resources with two other kinds of datasets: manually-tagged question reformulations and question-answer pairs. .