{"id":"https://openalex.org/W4388938354","doi":"https://doi.org/10.1109/icccnt56998.2023.10307351","title":"Abstractive Multi-Document Summarization: Exploiting Maximal Marginal Relevance and Pretrained Models","display_name":"Abstractive Multi-Document Summarization: Exploiting Maximal Marginal Relevance and Pretrained Models","publication_year":2023,"publication_date":"2023-07-06","ids":{"openalex":"https://openalex.org/W4388938354","doi":"https://doi.org/10.1109/icccnt56998.2023.10307351"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt56998.2023.10307351","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10307351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"type":"conference-abstract","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092571621","display_name":"Abdulrahman Mohsen Ahmed Zeyad","orcid":null},"institutions":[{"id":"https://openalex.org/I83737708","display_name":"REVA University","ror":"https://ror.org/03gtcxd54","country_code":"IN","type":"education","lineage":["https://openalex.org/I83737708"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abdulrahman Mohsen Ahmed Zeyad","raw_affiliation_strings":["REVA University,School of Computer Science and Engineering,Bangalore,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"REVA University,School of Computer Science and Engineering,Bangalore,India","institution_ids":["https://openalex.org/I83737708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026383984","display_name":"Arun Biradar","orcid":"https://orcid.org/0000-0003-2355-7066"},"institutions":[{"id":"https://openalex.org/I83737708","display_name":"REVA University","ror":"https://ror.org/03gtcxd54","country_code":"IN","type":"education","lineage":["https://openalex.org/I83737708"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Biradar","raw_affiliation_strings":["REVA University,School of Computer Science and Engineering,Bangalore,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"REVA University,School of Computer Science and Engineering,Bangalore,India","institution_ids":["https://openalex.org/I83737708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I83737708"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9977999925613403,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9480583071708679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7926391959190369},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7674353122711182},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5727201700210571},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5270374417304993},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49820899963378906},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4927239716053009},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46173250675201416},{"id":"https://openalex.org/keywords/rouge","display_name":"ROUGE","score":0.4442089796066284},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.41304171085357666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38524818420410156}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9480583071708679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7926391959190369},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7674353122711182},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5727201700210571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5270374417304993},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49820899963378906},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4927239716053009},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46173250675201416},{"id":"https://openalex.org/C7888048","wikidata":"https://www.wikidata.org/wiki/Q7277427","display_name":"ROUGE","level":2,"score":0.4442089796066284},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.41304171085357666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38524818420410156},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt56998.2023.10307351","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10307351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W912777836","https://openalex.org/W2154652894","https://openalex.org/W2904953531","https://openalex.org/W2946826359","https://openalex.org/W2962946054","https://openalex.org/W2963204221","https://openalex.org/W2970597249","https://openalex.org/W3013612165","https://openalex.org/W3015468748","https://openalex.org/W3034945650","https://openalex.org/W3034999214","https://openalex.org/W3106840321","https://openalex.org/W3138773240","https://openalex.org/W3157742697","https://openalex.org/W4226327346","https://openalex.org/W4288089799","https://openalex.org/W4301390649","https://openalex.org/W4320561696","https://openalex.org/W4324302588","https://openalex.org/W6682631176","https://openalex.org/W6748422325","https://openalex.org/W6763701032","https://openalex.org/W6769311223","https://openalex.org/W6771915120","https://openalex.org/W6776048684","https://openalex.org/W6849703526","https://openalex.org/W6850069386"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W2150160875","https://openalex.org/W2000777050","https://openalex.org/W4312318079","https://openalex.org/W2110921901","https://openalex.org/W2151695628","https://openalex.org/W2740913191"],"abstract_inverted_index":{"The":[0],"increasing":[1],"demand":[2],"for":[3,111,126],"effective":[4],"multi-document":[5],"summarization":[6,121],"(MDS)":[7],"due":[8],"to":[9,46],"the":[10,22,34,68,75,81,85,92,132],"rapid":[11],"expansion":[12],"of":[13,24,60,71,134],"information":[14],"availability":[15],"has":[16],"triggered":[17],"this":[18,45,90],"investigation.":[19],"Focused":[20],"on":[21,74,84],"fusion":[23],"Maximal":[25],"Marginal":[26],"Relevance":[27],"(MMR)":[28],"with":[29],"pretrained":[30],"models,":[31],"we":[32],"circumvented":[33],"often-cumbersome":[35],"fine-tuning":[36],"process,":[37],"and":[38,52,54,80,99,138],"introduced":[39],"a":[40],"novel":[41],"methodology.":[42],"We":[43],"applied":[44],"various":[47],"text":[48,120],"datasets":[49],"like":[50],"Multi-News":[51,76],"WCEP,":[53],"it":[55],"resulted":[56],"in":[57,136],"significant":[58],"improvement":[59],"ROUGE":[61],"scores,":[62],"illustrating":[63],"promising":[64],"results.":[65],"For":[66],"example,":[67],"ROUGE-1":[69,82],"score":[70,83],"our":[72],"method":[73],"dataset":[77,87],"was":[78,88],"46.23,":[79],"WCEP":[86],"30.74.In":[89],"discussion,":[91],"research":[93],"implications,":[94],"including":[95],"better":[96],"n-gram":[97],"optimization":[98],"model":[100,140],"selection":[101,141],"strategies,":[102],"were":[103],"brought":[104],"forward.":[105],"This":[106],"study":[107],"had":[108],"substantial":[109],"implications":[110],"natural":[112],"language":[113],"processing,":[114],"propelling":[115],"us":[116],"toward":[117],"more":[118],"advanced":[119],"applications,":[122],"presenting":[123],"potential":[124],"avenues":[125],"future":[127],"research,":[128],"such":[129],"as":[130],"refining":[131],"role":[133],"n-grams":[135],"summaries":[137],"optimizing":[139],"processes.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}