Related papers: Interactive Extractive Search over Biomedical Corpora

Interactive Extractive Search over Biomedical Corpora

URL: http://arxiv.org/abs/2006.04148v1
Date: Sun, 7 Jun 2020 13:26:32 GMT
Title: Interactive Extractive Search over Biomedical Corpora
Authors: Hillel Taub-Tabib, Micah Shlain, Shoval Sadde, Dan Lahav, Matan Eyal, Yaara Cohen, Yoav Goldberg
Abstract summary: We present a system that allows life-science researchers to search a linguistically annotated corpus of texts. We introduce a light-weight query language that does not require the user to know the details of the underlying linguistic representations. Search is performed at an interactive speed due to efficient linguistic graph-indexing and retrieval engine.
Score: 41.72755714431404
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: We present a system that allows life-science researchers to search a linguistically annotated corpus of scientific texts using patterns over dependency graphs, as well as using patterns over token sequences and a powerful variant of boolean keyword queries. In contrast to previous attempts to dependency-based search, we introduce a light-weight query language that does not require the user to know the details of the underlying linguistic representations, and instead to query the corpus by providing an example sentence coupled with simple markup. Search is performed at an interactive speed due to efficient linguistic graph-indexing and retrieval engine. This allows for rapid exploration, development and refinement of user queries. We demonstrate the system using example workflows over two corpora: the PubMed corpus including 14,446,243 PubMed abstracts and the CORD-19 dataset, a collection of over 45,000 research papers focused on COVID-19 research. The system is publicly available at https://allenai.github.io/spike

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