@inproceedings{8187c659665f4a56963305858aa17471,
title = "Vector Similarity of Related Words in the Japanese Word Net",
abstract = "Word2vec is a tool that produces vector representation of words from a large amount of text data. In this paper, we show that only a part of the vector space produced by word2vec is enough to represent the collective sense of a set of related words in the Japanese Word Net. Further, we will show that there is a subspace in the vector space which do not relate to the collective sense. We construct a compact decision tree by using the vectors in order to distinguish whether a given word belongs to the set of related words.",
author = "Takuya Hirao and Nao Wariishi and Takahiko Suzuki and Sachio Hirokawa",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 ; Conference date: 12-07-2015 Through 16-07-2015",
year = "2016",
month = jan,
day = "6",
doi = "10.1109/IIAI-AAI.2015.254",
language = "English",
series = "Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "142--147",
editor = "Sachio Hirokawa and Kiyota Hashimoto and Tokuro Matsuo and Tsunenori Mine",
booktitle = "Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015",
address = "United States",
}