@inproceedings{patel-etal-2020-use,
title = "On the Use of Web Search to Improve Scientific Collections",
author = "Patel, Krutarth and
Caragea, Cornelia and
Gollapalli, Sujatha Das",
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-1.20",
doi = "10.18653/v1/2020.sdp-1.20",
pages = "174--183",
abstract = "Despite the advancements in search engine features, ranking methods, technologies, and the availability of programmable APIs, current-day open-access digital libraries still rely on crawl-based approaches for acquiring their underlying document collections. In this paper, we propose a novel search-driven framework for acquiring documents for such scientific portals. Within our framework, publicly-available research paper titles and author names are used as queries to a Web search engine. We were able to obtain {\textasciitilde}267,000 unique research papers through our fully-automated framework using {\textasciitilde}76,000 queries, resulting in almost 200,000 more papers than the number of queries. Moreover, through a combination of title and author name search, we were able to recover 78{\%} of the original searched titles.",
}
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<abstract>Despite the advancements in search engine features, ranking methods, technologies, and the availability of programmable APIs, current-day open-access digital libraries still rely on crawl-based approaches for acquiring their underlying document collections. In this paper, we propose a novel search-driven framework for acquiring documents for such scientific portals. Within our framework, publicly-available research paper titles and author names are used as queries to a Web search engine. We were able to obtain 267,000 unique research papers through our fully-automated framework using 76,000 queries, resulting in almost 200,000 more papers than the number of queries. Moreover, through a combination of title and author name search, we were able to recover 78% of the original searched titles.</abstract>
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%0 Conference Proceedings
%T On the Use of Web Search to Improve Scientific Collections
%A Patel, Krutarth
%A Caragea, Cornelia
%A Gollapalli, Sujatha Das
%S Proceedings of the First Workshop on Scholarly Document Processing
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F patel-etal-2020-use
%X Despite the advancements in search engine features, ranking methods, technologies, and the availability of programmable APIs, current-day open-access digital libraries still rely on crawl-based approaches for acquiring their underlying document collections. In this paper, we propose a novel search-driven framework for acquiring documents for such scientific portals. Within our framework, publicly-available research paper titles and author names are used as queries to a Web search engine. We were able to obtain 267,000 unique research papers through our fully-automated framework using 76,000 queries, resulting in almost 200,000 more papers than the number of queries. Moreover, through a combination of title and author name search, we were able to recover 78% of the original searched titles.
%R 10.18653/v1/2020.sdp-1.20
%U https://aclanthology.org/2020.sdp-1.20
%U https://doi.org/10.18653/v1/2020.sdp-1.20
%P 174-183
Markdown (Informal)
[On the Use of Web Search to Improve Scientific Collections](https://aclanthology.org/2020.sdp-1.20) (Patel et al., sdp 2020)
ACL