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Embedding-based Scientific Literature Discovery in a Text Editor Application

Gökçe, Onur; Prada, Jonathan; Nikolov, Nikola I; Gu, Nianlong; Hahnloser, Richard H R (2020). Embedding-based Scientific Literature Discovery in a Text Editor Application. In: The 58th annual meeting of the Association for Computational Linguistics (ACL), Virtual Conference, 5 July 2020 - 10 July 2020, Association for Computational Linguistics.

Abstract

Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited. However, despite the availability of powerful search engines and sophisticated text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. To define comprehensive search queries requires strong motivation from authors, irrespective of their familiarity with the research field. Moreover, switching between independent applications for literature discovery, bibliography management, reading papers, and writing text burdens authors further and interrupts their creative process. Here, we present a web application that combines text editing and literatured iscovery in an interactive user interface. The application is equipped with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings, providing a discovery experience tuned to an author’s manuscript and his interests. Our application aims to take a step towards more enjoyable and effortless academic writing.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:10 July 2020
Deposited On:16 Feb 2021 08:29
Last Modified:08 May 2022 06:51
Publisher:Association for Computational Linguistics
OA Status:Green
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