{"id":"https://openalex.org/W3023380319","doi":"https://doi.org/10.1007/s11192-020-03455-z","title":"Cited text span identification for scientific summarisation using pre-trained encoders","display_name":"Cited text span identification for scientific summarisation using pre-trained encoders","publication_year":2020,"publication_date":"2020-05-07","ids":{"openalex":"https://openalex.org/W3023380319","doi":"https://doi.org/10.1007/s11192-020-03455-z","mag":"3023380319"},"language":"en","primary_location":{"id":"doi:10.1007/s11192-020-03455-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-020-03455-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-020-03455-z.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11192-020-03455-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004372721","display_name":"Chrysoula Zerva","orcid":"https://orcid.org/0000-0002-4031-9492"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Chrysoula Zerva","raw_affiliation_strings":["National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK"],"raw_orcid":"https://orcid.org/0000-0002-4031-9492","affiliations":[{"raw_affiliation_string":"National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042247568","display_name":"Minh-Quoc Nghiem","orcid":null},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Minh-Quoc Nghiem","raw_affiliation_strings":["National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050147609","display_name":"Nhung T. H. Nguyen","orcid":"https://orcid.org/0000-0001-5935-9235"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nhung T. H. Nguyen","raw_affiliation_strings":["National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077976343","display_name":"Sophia Ananiadou","orcid":"https://orcid.org/0000-0002-4097-9191"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sophia Ananiadou","raw_affiliation_strings":["Alan Turing Institute, London, UK","National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alan Turing Institute, London, UK","institution_ids":["https://openalex.org/I4210128584"]},{"raw_affiliation_string":"National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004372721"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":2.4166,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90877318,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"125","issue":"3","first_page":"3109","last_page":"3137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8335604667663574},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7590447664260864},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.67784583568573},{"id":"https://openalex.org/keywords/span","display_name":"Span (engineering)","score":0.67237389087677},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5520277619361877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280274748802185},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4928431510925293},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3818625211715698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3570771813392639}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8335604667663574},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7590447664260864},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.67784583568573},{"id":"https://openalex.org/C2778753569","wikidata":"https://www.wikidata.org/wiki/Q1960395","display_name":"Span (engineering)","level":2,"score":0.67237389087677},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5520277619361877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280274748802185},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4928431510925293},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3818625211715698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3570771813392639},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11192-020-03455-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-020-03455-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-020-03455-z.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/7e9e35e0-3fc6-4fe8-8713-2ffc68b8a3b8","is_oa":true,"landing_page_url":"https://research.manchester.ac.uk/en/publications/7e9e35e0-3fc6-4fe8-8713-2ffc68b8a3b8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Zerva, C, Nghiem, M, Nguyen, N T H & Ananiadou, S 2020, 'Cited text span identification for scientific summarisation using pre-trained encoders', Scientometrics. https://doi.org/10.1007/s11192-020-03455-z","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:RePEc:spr:scient:v:125:y:2020:i:3:d:10.1007_s11192-020-03455-z","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11192-020-03455-z","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s11192-020-03455-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-020-03455-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-020-03455-z.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.800000011920929}],"awards":[{"id":"https://openalex.org/G5318257804","display_name":"DTP 2016-2017 The University of Manchester","funder_award_id":"EP/N509565/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320325699","display_name":"Lloyd's Register","ror":null},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3023380319.pdf","grobid_xml":"https://content.openalex.org/works/W3023380319.grobid-xml"},"referenced_works_count":100,"referenced_works":["https://openalex.org/W179757531","https://openalex.org/W1520352740","https://openalex.org/W1536826708","https://openalex.org/W1559499673","https://openalex.org/W1566018662","https://openalex.org/W1832693441","https://openalex.org/W1848279521","https://openalex.org/W1870228376","https://openalex.org/W1970086395","https://openalex.org/W1974339500","https://openalex.org/W1975517671","https://openalex.org/W2054211469","https://openalex.org/W2081580037","https://openalex.org/W2083305840","https://openalex.org/W2085116970","https://openalex.org/W2088336913","https://openalex.org/W2101390659","https://openalex.org/W2104184715","https://openalex.org/W2116405309","https://openalex.org/W2153568396","https://openalex.org/W2157979304","https://openalex.org/W2160992478","https://openalex.org/W2166347079","https://openalex.org/W2178628967","https://openalex.org/W2250539671","https://openalex.org/W2251670640","https://openalex.org/W2252173290","https://openalex.org/W2252209912","https://openalex.org/W2295510082","https://openalex.org/W2510940142","https://openalex.org/W2566366613","https://openalex.org/W2571932860","https://openalex.org/W2572172445","https://openalex.org/W2572480699","https://openalex.org/W2572575571","https://openalex.org/W2572697031","https://openalex.org/W2572936957","https://openalex.org/W2574535369","https://openalex.org/W2593833795","https://openalex.org/W2606964149","https://openalex.org/W2606974598","https://openalex.org/W2611292523","https://openalex.org/W2612675303","https://openalex.org/W2768029001","https://openalex.org/W2768986464","https://openalex.org/W2771414034","https://openalex.org/W2771804720","https://openalex.org/W2774106686","https://openalex.org/W2775820860","https://openalex.org/W2790740913","https://openalex.org/W2801930304","https://openalex.org/W2808571346","https://openalex.org/W2883128308","https://openalex.org/W2887442908","https://openalex.org/W2887678570","https://openalex.org/W2887979973","https://openalex.org/W2887985752","https://openalex.org/W2896807716","https://openalex.org/W2898597872","https://openalex.org/W2899489554","https://openalex.org/W2905257126","https://openalex.org/W2916130807","https://openalex.org/W2922551710","https://openalex.org/W2944833000","https://openalex.org/W2950130316","https://openalex.org/W2950813464","https://openalex.org/W2952138241","https://openalex.org/W2953304564","https://openalex.org/W2954185263","https://openalex.org/W2962685628","https://openalex.org/W2962785754","https://openalex.org/W2962965405","https://openalex.org/W2963026768","https://openalex.org/W2963341956","https://openalex.org/W2963369195","https://openalex.org/W2963748441","https://openalex.org/W2966015053","https://openalex.org/W2966173823","https://openalex.org/W2966231147","https://openalex.org/W2966322300","https://openalex.org/W2969496316","https://openalex.org/W2970419734","https://openalex.org/W2972111982","https://openalex.org/W2973049837","https://openalex.org/W2979826702","https://openalex.org/W3099350049","https://openalex.org/W3105972515","https://openalex.org/W3138773240","https://openalex.org/W6630878475","https://openalex.org/W6675247125","https://openalex.org/W6682631176","https://openalex.org/W6731903645","https://openalex.org/W6731961142","https://openalex.org/W6746572399","https://openalex.org/W6746726881","https://openalex.org/W6753696220","https://openalex.org/W6753889038","https://openalex.org/W6766862601","https://openalex.org/W6785209554","https://openalex.org/W7057810606"],"related_works":["https://openalex.org/W4229054622","https://openalex.org/W4390516098","https://openalex.org/W4283651310","https://openalex.org/W4283803146","https://openalex.org/W4283792424","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W1981806906","https://openalex.org/W4205134996","https://openalex.org/W4205302943"],"abstract_inverted_index":{"Abstract":[0],"We":[1,25,105,189],"present":[2],"our":[3],"approach":[4],"for":[5,64,103],"the":[6,30,49,71,79,111,123,132,147,152,163,167,176,198,208],"identification":[7,72,129],"of":[8,32,73,81,86,125,166],"cited":[9,35,74,126,153,185,199],"text":[10,36,75,127,177],"spans":[11,37,178],"in":[12,19,40,84,192],"scientific":[13,68,133],"literature,":[14],"using":[15,33,92,196],"pre-trained":[16,59],"encoders":[17],"(BERT)":[18],"combination":[20],"with":[21],"different":[22,55,82,93,158],"neural":[23],"networks.":[24],"further":[26],"experiment":[27],"to":[28,57,67,146,183],"assess":[29,78],"impact":[31,80],"these":[34],"as":[38,170],"input":[39,148,171,209],"BERT-based":[41],"extractive":[42,138],"summarisation":[43,134,139],"methods.":[44],"Inspired":[45],"and":[46,91,95,101,109,172],"motivated":[47],"by":[48,186,195],"CL-SciSumm":[50],"shared":[51],"tasks,":[52],"we":[53,77,135,155,201],"explore":[54,156],"methods":[56],"adapt":[58],"models":[60,113],"which":[61],"are":[62],"tuned":[63],"generic":[65],"domain":[66,118],"literature.":[69],"For":[70,131],"spans,":[76],"configurations":[83],"terms":[85],"learning":[87],"from":[88,142,151],"augmented":[89,117],"data":[90,120],"features":[94],"network":[96],"architectures":[97],"(BERT,":[98],"XLNET,":[99],"CNN,":[100],"BiMPM)":[102],"training.":[104],"show":[106],"that":[107,179,191],"identifying":[108],"fine-tuning":[110],"language":[112],"on":[114],"unlabelled":[115],"or":[116],"specific":[119],"can":[121,202],"improve":[122],"performance":[124],"span":[128],"models.":[130],"implement":[136],"an":[137],"model":[140],"adapted":[141],"BERT.":[143],"With":[144],"respect":[145],"sentences":[149,164],"taken":[150],"paper,":[154],"two":[157],"scenarios:":[159],"(1)":[160],"consider":[161,174],"all":[162],"(full-text)":[165],"referenced":[168],"article":[169],"(2)":[173],"only":[175,197],"have":[180],"been":[181],"identified":[182],"be":[184],"other":[187],"publications.":[188],"observe":[190],"certain":[193],"experiments,":[194],"text-spans":[200],"achieve":[203],"better":[204],"performance,":[205],"while":[206],"minimising":[207],"size":[210],"needed.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}