{"id":"https://openalex.org/W4410436552","doi":"https://doi.org/10.1142/s1793351x25440015","title":"Translative Research Assistant: A Retrieval-Augmented Generation Pipeline Refinement with Keyword Extraction Using Extended Scalable Betweenness Centrality","display_name":"Translative Research Assistant: A Retrieval-Augmented Generation Pipeline Refinement with Keyword Extraction Using Extended Scalable Betweenness Centrality","publication_year":2025,"publication_date":"2025-05-16","ids":{"openalex":"https://openalex.org/W4410436552","doi":"https://doi.org/10.1142/s1793351x25440015"},"language":"en","primary_location":{"id":"doi:10.1142/s1793351x25440015","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793351x25440015","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"},"type":"article","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/A5018454631","display_name":"Chung-Hsien Chou","orcid":null},"institutions":[{"id":"https://openalex.org/I151934421","display_name":"University of Northern British Columbia","ror":"https://ror.org/025wzwv46","country_code":"CA","type":"education","lineage":["https://openalex.org/I151934421"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Chung-Hsien Chou","raw_affiliation_strings":["Samsung Canada, 565 Great Northern Way, Vancouver, British Columbia, Canada"],"affiliations":[{"raw_affiliation_string":"Samsung Canada, 565 Great Northern Way, Vancouver, British Columbia, Canada","institution_ids":["https://openalex.org/I151934421"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103663368","display_name":"Chee-Hann Wu","orcid":"https://orcid.org/0009-0008-5468-9014"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chee-Hann Wu","raw_affiliation_strings":["Department of Drama, New York University, New York, NY 10012, USA"],"affiliations":[{"raw_affiliation_string":"Department of Drama, New York University, New York, NY 10012, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018454631"],"corresponding_institution_ids":["https://openalex.org/I151934421"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05374099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"03","first_page":"413","last_page":"432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9986000061035156,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9986000061035156,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9193000197410583,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9172999858856201,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/betweenness-centrality","display_name":"Betweenness centrality","score":0.909511148929596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8783782720565796},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7432737350463867},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7262349128723145},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.577497661113739},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.5335679054260254},{"id":"https://openalex.org/keywords/keyword-extraction","display_name":"Keyword extraction","score":0.4394226670265198},{"id":"https://openalex.org/keywords/keyword-search","display_name":"Keyword search","score":0.41622394323349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3904377222061157},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3595580458641052},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.21198979020118713}],"concepts":[{"id":"https://openalex.org/C117045392","wikidata":"https://www.wikidata.org/wiki/Q4899215","display_name":"Betweenness centrality","level":3,"score":0.909511148929596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8783782720565796},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7432737350463867},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7262349128723145},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.577497661113739},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.5335679054260254},{"id":"https://openalex.org/C2780288562","wikidata":"https://www.wikidata.org/wiki/Q25053353","display_name":"Keyword extraction","level":2,"score":0.4394226670265198},{"id":"https://openalex.org/C2988412617","wikidata":"https://www.wikidata.org/wiki/Q7441656","display_name":"Keyword search","level":2,"score":0.41622394323349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3904377222061157},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3595580458641052},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.21198979020118713},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793351x25440015","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793351x25440015","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1550806611","https://openalex.org/W1971937094","https://openalex.org/W1983469497","https://openalex.org/W1985241583","https://openalex.org/W2109326195","https://openalex.org/W2113669181","https://openalex.org/W2122227111","https://openalex.org/W2133286915","https://openalex.org/W2143975166","https://openalex.org/W2167125846","https://openalex.org/W2319082423","https://openalex.org/W3043254550","https://openalex.org/W4244727960","https://openalex.org/W4254429331","https://openalex.org/W4385251138","https://openalex.org/W4386242492","https://openalex.org/W4393949013","https://openalex.org/W4394611549","https://openalex.org/W4406354911"],"related_works":["https://openalex.org/W1973509935","https://openalex.org/W4389076551","https://openalex.org/W2107855069","https://openalex.org/W2611574733","https://openalex.org/W2241641394","https://openalex.org/W2514739320","https://openalex.org/W2097992793","https://openalex.org/W2140653560","https://openalex.org/W2348831795","https://openalex.org/W4312461432"],"abstract_inverted_index":{"The":[0],"objective":[1],"of":[2,19,32,62,92,125,133,143],"this":[3],"research":[4,20,37],"is":[5,77,120],"to":[6,38,64,121],"introduce":[7],"a":[8,41,65,99],"translation":[9,18],"tool":[10],"that":[11],"addresses":[12],"two":[13],"critical":[14],"aspects:":[15],"first,":[16],"the":[17,30,60,70,78,90,104,123,131,141],"from":[21,35],"other":[22,36],"languages":[23],"into":[24],"our":[25,118],"target":[26],"language;":[27],"and":[28,56,129],"second,":[29],"adaptation":[31],"existing":[33],"knowledge":[34,100],"align":[39],"with":[40,108],"researcher\u2019s":[42,66],"specific":[43],"context.":[44],"To":[45,88],"achieve":[46],"this,":[47],"we":[48,96],"propose":[49],"these":[50],"key":[51],"approaches:":[52],"summarization,":[53],"keyword":[54,109],"extraction":[55,110],"evaluation,":[57],"which":[58],"assesses":[59],"relevance":[61],"materials":[63],"work":[67],"or":[68],"identifies":[69],"need":[71],"for":[72,98],"further":[73],"investigation.":[74],"Our":[75],"solution":[76],"Translative":[79],"Research":[80],"Assistant,":[81],"leveraging":[82],"ChatGPT":[83,134],"as":[84],"its":[85,93],"primary":[86],"tool.":[87],"enhance":[89,130],"accuracy":[91],"text":[94],"generation,":[95],"advocate":[97],"retrieval":[101],"approach":[102],"utilizing":[103],"Retrieval-Augmented":[105],"Generation":[106],"pipeline":[107],"using":[111],"proposed":[112],"Extended":[113],"Scalable":[114],"Betweenness":[115],"Centrality.":[116],"Ultimately,":[117],"aim":[119],"promote":[122],"integration":[124],"AI":[126],"across":[127],"disciplines":[128],"precision":[132],"responses,":[135],"aiding":[136],"researchers":[137],"in":[138],"efficiently":[139],"assessing":[140],"utility":[142],"new":[144],"information":[145],"they":[146],"encounter.":[147]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
