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Korean–Japanese story link detection based on distributional and contrastive properties of event terms
Authors:Kyung-Soon Lee  Kyo Kageura
Institution:1. Division of Electronics and Information Engineering, Chonbuk National University, 664-14 Duckjin-gu Jeonju, Jeonbuk 561-756, Republic of Korea;2. NII (National Institute of Informatics), 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo 101-8430, Japan
Abstract:In this paper, we propose a novel approach for multilingual story link detection. Our approach utilized the distributional features of terms in timelines and multilingual spaces, together with selected types of named entities in order to get distinctive weights for terms that constitute linguistic representation of events. On timelines term significance is calculated by comparing term distribution of the documents on a day with that of the total document collection. Since two languages can provide more information than one language, term significance is measured on each language space, which is then used as a bridge between two languages on multilingual spaces. Evaluating the method on Korean and Japanese news articles, our method achieved 14.3% improvement for monolingual story pairs, and 16.7% improvement for multilingual story pairs. By measuring the space density, the proposed weighting components are verified with a high density of the intra-event stories and a low density of the inter-events stories. This result indicates that the proposed method is helpful for multilingual story link detection.
Keywords:Story link detection  Event term  Multilingual space  Distributional property  Space density
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