no code implementations • WS 2018 • Michiharu Yamashita, Hideki Awashima, Hidekazu Oiwa
We built two research questions to clarify which types of entity matching systems works better than others.
no code implementations • 3 May 2018 • Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan
KOKO is novel in that its extraction language simultaneously supports conditions on the surface of the text and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions.
no code implementations • 1 Aug 2017 • Hidekazu Oiwa, Yoshihiko Suhara, Jiyu Komiya, Andrei Lopatenko
Entity population, a task of collecting entities that belong to a particular category, has attracted attention from vertical domains.
1 code implementation • 18 Jun 2017 • Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, Yuji Matsumoto
Knowledge base completion (KBC) aims to predict missing information in a knowledge base. In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC:how to answer queries concerning test entities not observed at training time.
no code implementations • NeurIPS 2014 • Hidekazu Oiwa, Ryohei Fujimaki
One of the key challenges in their use is non-convexity in simultaneous optimization of regions and region-specific models.