{"id":"https://openalex.org/W7160305530","doi":"https://doi.org/10.5753/sbsi.2026.248295","title":"A Generic Extractive Multi-document Text Summarization Method Using Memetic Algorithm and Combinatorial Optimization","display_name":"A Generic Extractive Multi-document Text Summarization Method Using Memetic Algorithm and Combinatorial Optimization","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160305530","doi":"https://doi.org/10.5753/sbsi.2026.248295"},"language":null,"primary_location":{"id":"doi:10.5753/sbsi.2026.248295","is_oa":true,"landing_page_url":"https://doi.org/10.5753/sbsi.2026.248295","pdf_url":"https://sol.sbc.org.br/index.php/sbsi/article/download/41317/41087","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Information Systems (SBSI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://sol.sbc.org.br/index.php/sbsi/article/download/41317/41087","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121889872","display_name":"Alysson Guimar\u00e3es","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alysson Guimar\u00e3es","raw_affiliation_strings":["UFS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFS","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025218993","display_name":"METHANIAS COLACO","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124990","display_name":"Faculdades Guarulhos","ror":"https://ror.org/02s6maw65","country_code":"BR","type":"other","lineage":["https://openalex.org/I4210124990"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Methanias Cola\u00e7o Junior","raw_affiliation_strings":["UFS / UFRN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFS / UFRN","institution_ids":["https://openalex.org/I4210124990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69153887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"81","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5491999983787537,"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":0.5491999983787537,"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":0.12929999828338623,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.06970000267028809,"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":0.9330000281333923},{"id":"https://openalex.org/keywords/memetic-algorithm","display_name":"Memetic algorithm","score":0.8180000185966492},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6676999926567078},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5943999886512756},{"id":"https://openalex.org/keywords/memetics","display_name":"Memetics","score":0.513700008392334},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42719998955726624},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.37369999289512634},{"id":"https://openalex.org/keywords/combinatorial-optimization","display_name":"Combinatorial optimization","score":0.36910000443458557}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9330000281333923},{"id":"https://openalex.org/C35129592","wikidata":"https://www.wikidata.org/wiki/Q324793","display_name":"Memetic algorithm","level":3,"score":0.8180000185966492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6823999881744385},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6676999926567078},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5943999886512756},{"id":"https://openalex.org/C51620047","wikidata":"https://www.wikidata.org/wiki/Q23399","display_name":"Memetics","level":2,"score":0.513700008392334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42719998955726624},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41100001335144043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C52692508","wikidata":"https://www.wikidata.org/wiki/Q1333872","display_name":"Combinatorial optimization","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C181335050","wikidata":"https://www.wikidata.org/wiki/Q14915018","display_name":"Swarm behaviour","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5753/sbsi.2026.248295","is_oa":true,"landing_page_url":"https://doi.org/10.5753/sbsi.2026.248295","pdf_url":"https://sol.sbc.org.br/index.php/sbsi/article/download/41317/41087","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Information Systems (SBSI)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5753/sbsi.2026.248295","is_oa":true,"landing_page_url":"https://doi.org/10.5753/sbsi.2026.248295","pdf_url":"https://sol.sbc.org.br/index.php/sbsi/article/download/41317/41087","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Information Systems (SBSI)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5508254170417786,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160305530.pdf","grobid_xml":"https://content.openalex.org/works/W7160305530.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W344004623","https://openalex.org/W1974321775","https://openalex.org/W1978394996","https://openalex.org/W1995875735","https://openalex.org/W2025825979","https://openalex.org/W2033409344","https://openalex.org/W2038411763","https://openalex.org/W2087573826","https://openalex.org/W2334966560","https://openalex.org/W2769676705","https://openalex.org/W2899410785","https://openalex.org/W3011262004","https://openalex.org/W3012254375","https://openalex.org/W3042185737","https://openalex.org/W3116797422","https://openalex.org/W3159094916","https://openalex.org/W3199838918","https://openalex.org/W4220785084","https://openalex.org/W4220916677","https://openalex.org/W4401946165","https://openalex.org/W4405193241","https://openalex.org/W4406942148"],"related_works":[],"abstract_inverted_index":{"Research":[0,131],"Context:Automatic":[1],"text":[2,45,111],"summarization":[3,18,112],"remains":[4],"a":[5,32,228,259],"subject":[6],"of":[7,35,43,69,156,191,213,255,275],"considerable":[8],"relevance":[9],"across":[10],"multiple":[11],"domains.":[12],"In":[13],"particular,":[14],"extractive":[15,108],"multi-document":[16,109],"generic":[17,107],"has":[19,51],"garnered":[20],"increased":[21],"attention":[22],"due":[23],"to":[24,27,76,104,139,224,237],"its":[25],"capacity":[26],"mitigate":[28],"information":[29,61],"overload":[30],"in":[31,54,60,134,152,193,197,215,219,249,279],"wide":[33],"range":[34],"applications.":[36],"Scientific":[37],"and/or":[38,82],"Practical":[39],"Problem:":[40],"The":[41,180],"volume":[42],"unstructured":[44],"data":[46,70],"produced":[47],"on":[48,162,199,232,265],"the":[49,90,99,106,142,146,153,163,172,184,200,205,208,242,253,256,267,273,276],"internet":[50],"grown":[52],"exponentially":[53],"recent":[55],"years,":[56],"driven":[57],"by":[58],"advances":[59],"and":[62,88,128,149,167,195,217,222,281],"communication":[63],"technologies":[64],"(ICTs).":[65],"This":[66,84,121],"massive":[67],"generation":[68],"makes":[71],"it":[72,251],"difficult":[73],"for":[74,175,241],"users":[75],"find":[77],"relevant":[78],"information.":[79],"Proposed":[80],"Solution":[81],"Analysis:":[83],"study":[85],"introduces,":[86],"implements,":[87],"applies":[89],"memetic":[91,126,229],"algorithm":[92,230],"known":[93],"as":[94,258],"Holistic":[95],"Text":[96],"Summarization":[97],"with":[98],"Shuffled":[100],"Frog-Leaping":[101],"Algorithm":[102],"(HSSFLA)":[103],"address":[105],"multi-language":[110],"problem":[113,240],"using":[114,171],"combinatorial":[115,129],"optimization":[116],"techniques.":[117],"Related":[118],"IS":[119,225],"Theory:":[120],"research":[122],"integrates":[123],"swarm":[124,233],"intelligence,":[125,234],"algorithms":[127],"optimization.":[130],"Method:":[132],"An":[133],"vitro":[135],"experiment":[136],"was":[137,169,235],"conducted":[138],"quantitatively":[140],"compare":[141],"summary":[143,257],"quality":[144,254],"between":[145],"proposed":[147,185],"method":[148,209],"similar":[150],"methods":[151],"literature.":[154],"Summary":[155],"Results:":[157],"Experiments":[158],"were":[159],"carried":[160],"out":[161],"DUC2001/2002":[164],"benchmark":[165],"datasets,":[166],"performance":[168],"evaluated":[170],"Recall-Oriented":[173],"Understudy":[174],"Gisting":[176],"Evaluation":[177],"(ROUGE)":[178],"metric.":[179],"results":[181,274],"demonstrate":[182],"that":[183],"approach":[186],"yielded":[187],"an":[188],"average":[189,211],"improvement":[190],"25.12%":[192],"ROUGE-1":[194,216],"34.91%":[196],"ROUGE-2":[198],"DUC":[201],"2001":[202],"dataset.":[203],"On":[204],"DUC2002":[206],"dataset,":[207],"achieved":[210],"gains":[212],"35.42%":[214],"36.08%":[218],"ROUGE-2.":[220],"Contributions":[221],"Impact":[223],"area:":[226],"HSSFLA,":[227],"based":[231],"developed":[236],"solve":[238],"this":[239],"first":[243],"time.":[244],"It":[245],"creates":[246],"holistic":[247],"summaries,":[248],"which":[250],"evaluates":[252],"whole,":[260],"rather":[261],"than":[262],"focusing":[263],"exhaustively":[264],"finding":[266],"best":[268],"individual":[269],"sentences.":[270],"HSSFLA":[271],"outperforms":[272],"scientific":[277],"literature":[278],"DUC2001":[280],"DUC2002.":[282]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}