@inproceedings{ding-etal-2020-cydex,
title = "Cydex: Neural Search Infrastructure for the Scholarly Literature",
author = "Ding, Shane and
Zhang, Edwin and
Lin, Jimmy",
editor = "Chandrasekaran, Muthu Kumar and
de Waard, Anita and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Hovy, Eduard and
Knoth, Petr and
Konopnicki, David and
Mayr, Philipp and
Patton, Robert M. and
Shmueli-Scheuer, Michal",
booktitle = "Proceedings of the First Workshop on Scholarly Document Processing",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.sdp-1.19/",
doi = "10.18653/v1/2020.sdp-1.19",
pages = "168--173",
abstract = "Cydex is a platform that provides neural search infrastructure for domain-specific scholarly literature. The platform represents an abstraction of Covidex, our recently developed full-stack open-source search engine for the COVID-19 Open Research Dataset (CORD-19) from AI2. While Covidex takes advantage of the latest best practices for keyword search using the popular Lucene search library as well as state-of-the-art neural ranking models using T5, parts of the system were hard coded to only work with CORD-19. This paper describes our efforts to generalize Covidex into Cydex, which can be applied to scholarly literature in different domains. By decoupling corpus-specific configurations from the frontend implementation, we are able to demonstrate the generality of Cydex on two very different corpora: the ACL Anthology and a collection of hydrology abstracts. Our platform is entirely open source and available at cydex.ai."
}
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<abstract>Cydex is a platform that provides neural search infrastructure for domain-specific scholarly literature. The platform represents an abstraction of Covidex, our recently developed full-stack open-source search engine for the COVID-19 Open Research Dataset (CORD-19) from AI2. While Covidex takes advantage of the latest best practices for keyword search using the popular Lucene search library as well as state-of-the-art neural ranking models using T5, parts of the system were hard coded to only work with CORD-19. This paper describes our efforts to generalize Covidex into Cydex, which can be applied to scholarly literature in different domains. By decoupling corpus-specific configurations from the frontend implementation, we are able to demonstrate the generality of Cydex on two very different corpora: the ACL Anthology and a collection of hydrology abstracts. Our platform is entirely open source and available at cydex.ai.</abstract>
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%0 Conference Proceedings
%T Cydex: Neural Search Infrastructure for the Scholarly Literature
%A Ding, Shane
%A Zhang, Edwin
%A Lin, Jimmy
%Y Chandrasekaran, Muthu Kumar
%Y de Waard, Anita
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Hovy, Eduard
%Y Knoth, Petr
%Y Konopnicki, David
%Y Mayr, Philipp
%Y Patton, Robert M.
%Y Shmueli-Scheuer, Michal
%S Proceedings of the First Workshop on Scholarly Document Processing
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F ding-etal-2020-cydex
%X Cydex is a platform that provides neural search infrastructure for domain-specific scholarly literature. The platform represents an abstraction of Covidex, our recently developed full-stack open-source search engine for the COVID-19 Open Research Dataset (CORD-19) from AI2. While Covidex takes advantage of the latest best practices for keyword search using the popular Lucene search library as well as state-of-the-art neural ranking models using T5, parts of the system were hard coded to only work with CORD-19. This paper describes our efforts to generalize Covidex into Cydex, which can be applied to scholarly literature in different domains. By decoupling corpus-specific configurations from the frontend implementation, we are able to demonstrate the generality of Cydex on two very different corpora: the ACL Anthology and a collection of hydrology abstracts. Our platform is entirely open source and available at cydex.ai.
%R 10.18653/v1/2020.sdp-1.19
%U https://aclanthology.org/2020.sdp-1.19/
%U https://doi.org/10.18653/v1/2020.sdp-1.19
%P 168-173
Markdown (Informal)
[Cydex: Neural Search Infrastructure for the Scholarly Literature](https://aclanthology.org/2020.sdp-1.19/) (Ding et al., sdp 2020)
ACL