| Presentation | 2019-06-01 Jointly Embedding Knowledge Graph and Feature in Vector Space Tomu Kadoki, Runhe Huang, Satoru Fujita, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Knowledge Graph, utilized in search engine, can be embed in a low dimensional vector space with knowledge graph embedding model. The traditional approach for knowledge graph embedding model could hardly express overloading meaning in entities. In this paper, we propose WKmodel that embeds similarity in the word representation in vector space into the knowledge graph embedding model. We compared WKmodel with TransE in terms of the performance of knowledge graph and similarities between the embedding model and the word representation in vector space. There are two results shown in this paper; WKmodel can embed similarity of word representation in the vector space with knowledge, and achieves the balanced performance in entity prediction by embedding the similarity measure from knowledge. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Knowledge graph / Knowledge embedding model / Word vector / Entity prediction / Word similarity |
| Paper # | SC2019-10 |
| Date of Issue | 2019-05-24 (SC) |
| Conference Information | |
| Committee | SC |
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| Conference Date | 2019/5/31(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | National Institute for Materials Science |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Science Service Platform, Data Service and Machine Learning, etc |
| Chair | Masahide Nakamura(Kobe Univ.) |
| Vice Chair | Shinji Kikuchi(National Institute for Materials Science) / Yoji Yamato(NTT) |
| Secretary | Shinji Kikuchi(Tokyo University of Technology) / Yoji Yamato(Fujitsu Lab.) |
| Assistant | |
| Paper Information | |
| Registration To | Technical Committee on Service Computing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Jointly Embedding Knowledge Graph and Feature in Vector Space |
| Sub Title (in English) | |
| Keyword(1) | Knowledge graph |
| Keyword(2) | Knowledge embedding model |
| Keyword(3) | Word vector |
| Keyword(4) | Entity prediction |
| Keyword(5) | Word similarity |
| 1st Author's Name | Tomu Kadoki |
| 1st Author's Affiliation | Hosei University(Hosei Univ.) |
| 2nd Author's Name | Runhe Huang |
| 2nd Author's Affiliation | Hosei University(Hosei Univ.) |
| 3rd Author's Name | Satoru Fujita |
| 3rd Author's Affiliation | Hosei University(Hosei Univ.) |
| Date | 2019-06-01 |
| Paper # | SC2019-10 |
| Volume (vol) | vol.119 |
| Number (no) | SC-66 |
| Page | pp.pp.55-60(SC), |
| #Pages | 6 |
| Date of Issue | 2019-05-24 (SC) |