Scientific Article Search System Based on Discourse Facet Representation
Abstract
We present a browser-based scientific article search system with graphical visualization. This system is based on triples of distributed representations of articles, each triple representing a scientific discourse facet (Objective, Method, or Result) using both text and citation information. Because each facet of an article is encoded as a separate vector, the similarity between articles can be measured by considering the articles not only in their entirety but also on a facet-by-facet basis. Our system provides three search options: a similarity ranking search, a citation graph with facet-labeled edges, and a scatter plot visualization with facets as the axes.
Cite
Text
Kobayashi et al. "Scientific Article Search System Based on Discourse Facet Representation." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019859Markdown
[Kobayashi et al. "Scientific Article Search System Based on Discourse Facet Representation." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/kobayashi2019aaai-scientific/) doi:10.1609/AAAI.V33I01.33019859BibTeX
@inproceedings{kobayashi2019aaai-scientific,
title = {{Scientific Article Search System Based on Discourse Facet Representation}},
author = {Kobayashi, Yuta and Shindo, Hiroyuki and Matsumoto, Yuji},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {9859-9860},
doi = {10.1609/AAAI.V33I01.33019859},
url = {https://mlanthology.org/aaai/2019/kobayashi2019aaai-scientific/}
}