A term-based and citation network-based search system for COVID-19
The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified...
Gespeichert in:
Veröffentlicht in: | JAMIA open 2021-10, Vol.4 (4), p.ooab104-ooab104 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | ooab104 |
---|---|
container_issue | 4 |
container_start_page | ooab104 |
container_title | JAMIA open |
container_volume | 4 |
creator | Zerva, Chrysoula Taylor, Samuel Soto, Axel J Nguyen, Nhung T H Ananiadou, Sophia |
description | The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/. |
doi_str_mv | 10.1093/jamiaopen/ooab104 |
format | Article |
fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8672931</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A778908450</galeid><sourcerecordid>A778908450</sourcerecordid><originalsourceid>FETCH-LOGICAL-c466t-5f6f755e6e8521dde478bd3fe039d486dc24097271c96c7285677eab90311e453</originalsourceid><addsrcrecordid>eNptkU9rGzEQxUVpqEOSD9BLWeill431X6tLwXWSJhDIJelVaKVZR-6u5Errlnz7bLBrEghz0DDze48RD6HPBJ8TrNl8bYdg0wbiPCXbEsw_oGMqFK-pYOTjq36GzkpZY4yJ1loy_AnNGNdUYUyP0Y9FNUIe6tYW8JWNvnJhtGNIsYow_kv5935VwGb3WJWnMsJQdSlXy7tfNxc10afoqLN9gbP9e4Ieri7vl9f17d3Pm-XitnZcyrEWneyUECChEZR4D1w1rWcdYKY9b6R3lGOtqCJOS6doI6RSYFuNGSHABTtB33e-m207gHcQx2x7s8lhsPnJJBvM200Mj2aV_ppGKqoZmQy-7Q1y-rOFMpohFAd9byOkbTFUEoq5mo6Y0K87dGV7MCF2aXJ0L7hZKNVo3HCBJ-r8HWoqD0NwKUIXpvkbAdkJXE6lZOgO1xNsXlI1h1TNPtVJ8-X1tw-K_xmyZyHCnsE</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2612047097</pqid></control><display><type>article</type><title>A term-based and citation network-based search system for COVID-19</title><source>DOAJ Directory of Open Access Journals</source><source>Access via Oxford University Press (Open Access Collection)</source><source>Oxford University Press Journals All Titles (1996-Current)</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Zerva, Chrysoula ; Taylor, Samuel ; Soto, Axel J ; Nguyen, Nhung T H ; Ananiadou, Sophia</creator><creatorcontrib>Zerva, Chrysoula ; Taylor, Samuel ; Soto, Axel J ; Nguyen, Nhung T H ; Ananiadou, Sophia</creatorcontrib><description>The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/.</description><identifier>ISSN: 2574-2531</identifier><identifier>EISSN: 2574-2531</identifier><identifier>DOI: 10.1093/jamiaopen/ooab104</identifier><identifier>PMID: 34927002</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Analysis ; Application Notes ; Computational linguistics ; Development and progression ; Epidemics ; Epidemiologists ; Language processing ; Natural language interfaces ; United Kingdom ; Visualization (Computers)</subject><ispartof>JAMIA open, 2021-10, Vol.4 (4), p.ooab104-ooab104</ispartof><rights>The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.</rights><rights>COPYRIGHT 2021 Oxford University Press</rights><rights>The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c466t-5f6f755e6e8521dde478bd3fe039d486dc24097271c96c7285677eab90311e453</citedby><cites>FETCH-LOGICAL-c466t-5f6f755e6e8521dde478bd3fe039d486dc24097271c96c7285677eab90311e453</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672931/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672931/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,729,782,786,866,887,27931,27932,53798,53800</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34927002$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zerva, Chrysoula</creatorcontrib><creatorcontrib>Taylor, Samuel</creatorcontrib><creatorcontrib>Soto, Axel J</creatorcontrib><creatorcontrib>Nguyen, Nhung T H</creatorcontrib><creatorcontrib>Ananiadou, Sophia</creatorcontrib><title>A term-based and citation network-based search system for COVID-19</title><title>JAMIA open</title><addtitle>JAMIA Open</addtitle><description>The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/.</description><subject>Analysis</subject><subject>Application Notes</subject><subject>Computational linguistics</subject><subject>Development and progression</subject><subject>Epidemics</subject><subject>Epidemiologists</subject><subject>Language processing</subject><subject>Natural language interfaces</subject><subject>United Kingdom</subject><subject>Visualization (Computers)</subject><issn>2574-2531</issn><issn>2574-2531</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNptkU9rGzEQxUVpqEOSD9BLWeill431X6tLwXWSJhDIJelVaKVZR-6u5Errlnz7bLBrEghz0DDze48RD6HPBJ8TrNl8bYdg0wbiPCXbEsw_oGMqFK-pYOTjq36GzkpZY4yJ1loy_AnNGNdUYUyP0Y9FNUIe6tYW8JWNvnJhtGNIsYow_kv5935VwGb3WJWnMsJQdSlXy7tfNxc10afoqLN9gbP9e4Ieri7vl9f17d3Pm-XitnZcyrEWneyUECChEZR4D1w1rWcdYKY9b6R3lGOtqCJOS6doI6RSYFuNGSHABTtB33e-m207gHcQx2x7s8lhsPnJJBvM200Mj2aV_ppGKqoZmQy-7Q1y-rOFMpohFAd9byOkbTFUEoq5mo6Y0K87dGV7MCF2aXJ0L7hZKNVo3HCBJ-r8HWoqD0NwKUIXpvkbAdkJXE6lZOgO1xNsXlI1h1TNPtVJ8-X1tw-K_xmyZyHCnsE</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>Zerva, Chrysoula</creator><creator>Taylor, Samuel</creator><creator>Soto, Axel J</creator><creator>Nguyen, Nhung T H</creator><creator>Ananiadou, Sophia</creator><general>Oxford University Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20211001</creationdate><title>A term-based and citation network-based search system for COVID-19</title><author>Zerva, Chrysoula ; Taylor, Samuel ; Soto, Axel J ; Nguyen, Nhung T H ; Ananiadou, Sophia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c466t-5f6f755e6e8521dde478bd3fe039d486dc24097271c96c7285677eab90311e453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analysis</topic><topic>Application Notes</topic><topic>Computational linguistics</topic><topic>Development and progression</topic><topic>Epidemics</topic><topic>Epidemiologists</topic><topic>Language processing</topic><topic>Natural language interfaces</topic><topic>United Kingdom</topic><topic>Visualization (Computers)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zerva, Chrysoula</creatorcontrib><creatorcontrib>Taylor, Samuel</creatorcontrib><creatorcontrib>Soto, Axel J</creatorcontrib><creatorcontrib>Nguyen, Nhung T H</creatorcontrib><creatorcontrib>Ananiadou, Sophia</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>JAMIA open</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zerva, Chrysoula</au><au>Taylor, Samuel</au><au>Soto, Axel J</au><au>Nguyen, Nhung T H</au><au>Ananiadou, Sophia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A term-based and citation network-based search system for COVID-19</atitle><jtitle>JAMIA open</jtitle><addtitle>JAMIA Open</addtitle><date>2021-10-01</date><risdate>2021</risdate><volume>4</volume><issue>4</issue><spage>ooab104</spage><epage>ooab104</epage><pages>ooab104-ooab104</pages><issn>2574-2531</issn><eissn>2574-2531</eissn><abstract>The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>34927002</pmid><doi>10.1093/jamiaopen/ooab104</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2574-2531 |
ispartof | JAMIA open, 2021-10, Vol.4 (4), p.ooab104-ooab104 |
issn | 2574-2531 2574-2531 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8672931 |
source | DOAJ Directory of Open Access Journals; Access via Oxford University Press (Open Access Collection); Oxford University Press Journals All Titles (1996-Current); EZB-FREE-00999 freely available EZB journals; PubMed Central |
subjects | Analysis Application Notes Computational linguistics Development and progression Epidemics Epidemiologists Language processing Natural language interfaces United Kingdom Visualization (Computers) |
title | A term-based and citation network-based search system for COVID-19 |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-05T07%3A41%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20term-based%20and%20citation%20network-based%20search%20system%20for%20COVID-19&rft.jtitle=JAMIA%20open&rft.au=Zerva,%20Chrysoula&rft.date=2021-10-01&rft.volume=4&rft.issue=4&rft.spage=ooab104&rft.epage=ooab104&rft.pages=ooab104-ooab104&rft.issn=2574-2531&rft.eissn=2574-2531&rft_id=info:doi/10.1093/jamiaopen/ooab104&rft_dat=%3Cgale_pubme%3EA778908450%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2612047097&rft_id=info:pmid/34927002&rft_galeid=A778908450&rfr_iscdi=true |