Bib2vec: An Embedding-based Search System For Bibliographic Information | Awesome Learning to Hash Add your paper to Learning2Hash

Bib2vec: An Embedding-based Search System For Bibliographic Information

Takuma Yoneda, Koki Mori, Makoto Miwa, Yutaka Sasaki . Proceedings of the EACL 2017 Software Demonstrations Valencia Spain April 3-7 2017 pages 112-115 2017 – 1 citation

[Paper]   Search on Google Scholar   Search on Semantic Scholar
Evaluation

We propose a novel embedding model that represents relationships among several elements in bibliographic information with high representation ability and flexibility. Based on this model, we present a novel search system that shows the relationships among the elements in the ACL Anthology Reference Corpus. The evaluation results show that our model can achieve a high prediction ability and produce reasonable search results.

Similar Work