{"id":"https://openalex.org/W4389711618","doi":"https://doi.org/10.7717/peerj-cs.1737","title":"Multi-granularity adaptive extractive document summarization with heterogeneous graph neural networks","display_name":"Multi-granularity adaptive extractive document summarization with heterogeneous graph neural networks","publication_year":2023,"publication_date":"2023-12-13","ids":{"openalex":"https://openalex.org/W4389711618","doi":"https://doi.org/10.7717/peerj-cs.1737","pmid":"https://pubmed.ncbi.nlm.nih.gov/38192460"},"language":"en","primary_location":{"id":"doi:10.7717/peerj-cs.1737","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1737","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.7717/peerj-cs.1737","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001141102","display_name":"Wu Chung Su","orcid":"https://orcid.org/0000-0002-8229-4799"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Su","raw_affiliation_strings":["School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China"],"raw_orcid":"https://orcid.org/0000-0002-8229-4799","affiliations":[{"raw_affiliation_string":"School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111241672","display_name":"Jin Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Jiang","raw_affiliation_strings":["School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101033541","display_name":"Kaihui Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaihui Huang","raw_affiliation_strings":["School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electronic Information, Xiangtan University, Xiangtan, Hunan Province, China","institution_ids":["https://openalex.org/I4610292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4610292"],"apc_list":{"value":1395,"currency":"USD","value_usd":1395},"apc_paid":{"value":1395,"currency":"USD","value_usd":1395},"fwci":0.7907,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78433703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"e1737","last_page":"e1737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.801682710647583},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.767817497253418},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6172702312469482},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5758768320083618},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5056836605072021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45972415804862976},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41400620341300964},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29130110144615173}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801682710647583},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.767817497253418},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6172702312469482},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5758768320083618},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5056836605072021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45972415804862976},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41400620341300964},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29130110144615173},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.7717/peerj-cs.1737","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1737","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},{"id":"pmid:38192460","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38192460","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ. Computer science","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10773739","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10773739","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10773739/pdf/peerj-cs-09-1737.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Comput Sci","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:82d69208f841443eb4b88c6fbd78aa34","is_oa":true,"landing_page_url":"https://doaj.org/article/82d69208f841443eb4b88c6fbd78aa34","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PeerJ Computer Science, Vol 9, p e1737 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.7717/peerj-cs.1737","is_oa":true,"landing_page_url":"https://doi.org/10.7717/peerj-cs.1737","pdf_url":null,"source":{"id":"https://openalex.org/S4210178049","display_name":"PeerJ Computer Science","issn_l":"2376-5992","issn":["2376-5992"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320104","host_organization_name":"PeerJ, Inc.","host_organization_lineage":["https://openalex.org/P4310320104"],"host_organization_lineage_names":["PeerJ, Inc."],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PeerJ Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.699999988079071,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1525595230","https://openalex.org/W1614298861","https://openalex.org/W2032797450","https://openalex.org/W2069618502","https://openalex.org/W2112796928","https://openalex.org/W2149795409","https://openalex.org/W2154652894","https://openalex.org/W2250539671","https://openalex.org/W2255466643","https://openalex.org/W2562609730","https://openalex.org/W2606780347","https://openalex.org/W2612675303","https://openalex.org/W2890747986","https://openalex.org/W2896457183","https://openalex.org/W2913991091","https://openalex.org/W2924690340","https://openalex.org/W2941263658","https://openalex.org/W2945408430","https://openalex.org/W2947881255","https://openalex.org/W2949423646","https://openalex.org/W2949615363","https://openalex.org/W2949938674","https://openalex.org/W2950635152","https://openalex.org/W2951623480","https://openalex.org/W2951777553","https://openalex.org/W2952138241","https://openalex.org/W2952829147","https://openalex.org/W2963045354","https://openalex.org/W2963919031","https://openalex.org/W2963929190","https://openalex.org/W2969740599","https://openalex.org/W2970398671","https://openalex.org/W2971200279","https://openalex.org/W2976106086","https://openalex.org/W3016613551","https://openalex.org/W3019556061","https://openalex.org/W3035647909","https://openalex.org/W3100053428","https://openalex.org/W3138773240","https://openalex.org/W3176319847","https://openalex.org/W4237791300","https://openalex.org/W4286795917","https://openalex.org/W4287610089","https://openalex.org/W4288336326","https://openalex.org/W4289665902","https://openalex.org/W4289799648","https://openalex.org/W4297229699","https://openalex.org/W4297733535","https://openalex.org/W4300665782","https://openalex.org/W4316038822","https://openalex.org/W4319653520","https://openalex.org/W4385245566","https://openalex.org/W6631501603","https://openalex.org/W6632455782","https://openalex.org/W6658537365","https://openalex.org/W6667681184","https://openalex.org/W6671387458","https://openalex.org/W6682631176","https://openalex.org/W6691431627","https://openalex.org/W6731948947","https://openalex.org/W6736685754","https://openalex.org/W6739901393","https://openalex.org/W6761497217","https://openalex.org/W6767206003","https://openalex.org/W6767425499","https://openalex.org/W6779342539","https://openalex.org/W6785305436","https://openalex.org/W6785421358","https://openalex.org/W6792943531"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W3148229873","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W2091301346","https://openalex.org/W1517524280","https://openalex.org/W4389760904","https://openalex.org/W4306886878","https://openalex.org/W4323520239"],"abstract_inverted_index":{"The":[0],"crucial":[1],"aspect":[2],"of":[3,19,37,55,61,76,85,91,107,115,147,185,190,205,223,235],"extractive":[4],"document":[5,111],"summarization":[6],"lies":[7],"in":[8,34,40,109,168,188,214,220],"understanding":[9],"the":[10,28,35,41,53,59,83,89,105,127,140,169,179,202,206,221,232,240],"interrelations":[11],"between":[12,30,183],"sentences.":[13],"Documents":[14],"inherently":[15],"comprise":[16],"a":[17,110,113,117],"multitude":[18],"sentences,":[20,32],"and":[21,126,151,162,181,193],"sentence-level":[22,56],"models":[23],"frequently":[24],"fail":[25],"to":[26,48,98,122,153,177,216],"consider":[27],"relationships":[29,167],"distantly-placed":[31],"resulting":[33],"omission":[36],"significant":[38],"information":[39,44,170],"summary.":[42],"Moreover,":[43],"within":[45],"documents":[46,150],"tends":[47],"be":[49],"distributed":[50],"sparsely,":[51],"challenging":[52],"efficacy":[54],"models.":[57,226],"In":[58],"realm":[60],"heterogeneous":[62],"graph":[63,93],"neural":[64],"networks,":[65],"it":[66],"has":[67],"been":[68],"observed":[69],"that":[70],"semantic":[71,80],"nodes":[72,143,157,184],"with":[73,133,144],"varying":[74],"levels":[75,146],"granularity":[77],"encapsulate":[78],"distinct":[79],"connections.":[81],"Initially,":[82],"incorporation":[84],"edge":[86],"features":[87,125],"into":[88],"computation":[90],"dynamic":[92],"attention":[94],"networks":[95],"is":[96,120],"performed":[97],"account":[99],"for":[100,164],"node":[101],"relationships.":[102],"Subsequently,":[103],"given":[104],"multiplicity":[106],"topics":[108,132,152],"or":[112],"set":[114],"documents,":[116],"topic":[118],"model":[119,141],"employed":[121],"extract":[123],"topic-specific":[124],"probability":[128],"distribution":[129],"linking":[130],"these":[131,155],"sentence":[134],"nodes.":[135],"Last":[136],"but":[137],"not":[138],"least,":[139],"defines":[142],"different":[145,159,186],"granularity-ranging":[148],"from":[149,197],"sentences-and":[154],"various":[156],"necessitate":[158],"propagation":[160],"widths":[161],"depths":[163],"capturing":[165],"intricate":[166],"being":[171],"disseminated.":[172],"Adaptive":[173],"measures":[174],"are":[175],"taken":[176],"learn":[178],"importance":[180],"correlation":[182],"granularities":[187],"terms":[189],"both":[191],"width":[192],"depth.":[194],"Experimental":[195],"evidence":[196],"two":[198],"benchmark":[199],"datasets":[200],"highlights":[201],"superior":[203],"performance":[204],"proposed":[207],"model,":[208],"as":[209],"assessed":[210],"by":[211],"ROUGE":[212,242],"metrics,":[213],"comparison":[215],"existing":[217],"approaches,":[218],"even":[219],"absence":[222],"pre-trained":[224],"language":[225],"Additionally,":[227],"an":[228],"ablation":[229],"study":[230],"confirms":[231],"positive":[233],"impact":[234],"each":[236],"individual":[237],"module":[238],"on":[239],"model's":[241],"scores.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}