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.
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