{"id":"https://openalex.org/W4408258306","doi":"https://doi.org/10.1109/tencon61640.2024.10902869","title":"Human-Centered Intention Refinement for LLM-based Domain-Data Analysis Using Iterative Prompt Generation","display_name":"Human-Centered Intention Refinement for LLM-based Domain-Data Analysis Using Iterative Prompt Generation","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4408258306","doi":"https://doi.org/10.1109/tencon61640.2024.10902869"},"language":"en","primary_location":{"id":"doi:10.1109/tencon61640.2024.10902869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-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/A5116561205","display_name":"Daichi Ohnami","orcid":null},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daichi Ohnami","raw_affiliation_strings":["University of Aizu,Dept. Computer Science and Engineering,Aizuwakamatsu,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Aizu,Dept. Computer Science and Engineering,Aizuwakamatsu,Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068388221","display_name":"Rentaro Yoshioka","orcid":"https://orcid.org/0000-0003-0858-4867"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rentaro Yoshioka","raw_affiliation_strings":["University of Aizu,Dept. Computer Science and Engineering,Aizuwakamatsu,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Aizu,Dept. Computer Science and Engineering,Aizuwakamatsu,Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057532667","display_name":"Takayuki Hoshino","orcid":"https://orcid.org/0000-0003-4376-7853"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takayuki Hoshino","raw_affiliation_strings":["BIPROGY Inc.,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BIPROGY Inc.,Tokyo,Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24129671,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1368","last_page":"1372"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.9876999855041504,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.9876999855041504,"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/T14025","display_name":"Educational Technology and Assessment","score":0.9563000202178955,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9531000256538391,"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":0.6907072067260742},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5046852827072144},{"id":"https://openalex.org/keywords/iterative-refinement","display_name":"Iterative refinement","score":0.48551225662231445},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4250040650367737},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27214276790618896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09717404842376709}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6907072067260742},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5046852827072144},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.48551225662231445},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4250040650367737},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27214276790618896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09717404842376709},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon61640.2024.10902869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2314181201","https://openalex.org/W4379277977","https://openalex.org/W4388191413","https://openalex.org/W4388483152"],"related_works":["https://openalex.org/W2788561539","https://openalex.org/W1771726367","https://openalex.org/W2034475059","https://openalex.org/W144062141","https://openalex.org/W3006775069","https://openalex.org/W2895720711","https://openalex.org/W2159155511","https://openalex.org/W82507644","https://openalex.org/W2528330837","https://openalex.org/W1562083549"],"abstract_inverted_index":{"An":[0,92],"intention":[1,109],"refinement":[2],"method":[3],"for":[4],"domain-data":[5],"analysis":[6,56,67],"using":[7],"large":[8],"language":[9],"models":[10],"is":[11,75],"proposed.":[12],"It":[13],"employs":[14],"a":[15,20],"\u201cdomain-framing":[16],"prompt\u201d":[17],"to":[18,41,48,62,82,107],"relate":[19],"domain":[21,26,51,84],"expert's":[22],"interests":[23,102],"with":[24,88],"relevant":[25],"data.":[27],"The":[28,45,69],"initial":[29],"responses":[30],"are":[31],"followed":[32],"by":[33],"\u201cprobing":[34],"prompts\u201d":[35],"that":[36,58],"suggest":[37],"possible":[38],"follow-up":[39],"questions":[40,106],"provide":[42],"further":[43],"insight.":[44],"suggestions":[46],"aim":[47],"support":[49,83],"the":[50,76,96],"expert":[52],"in":[53,86,99],"recognizing":[54],"alternative":[55],"steps":[57],"may":[59],"be":[60],"difficult":[61],"notice":[63],"depending":[64],"on":[65],"their":[66],"skills.":[68],"main":[70],"contribution":[71],"of":[72,78],"this":[73,79],"study":[74],"proposal":[77],"human-centered":[80],"process":[81],"experts":[85],"interacting":[87],"an":[89],"LLM":[90],"effectively.":[91],"experimental":[93],"implementation":[94],"demonstrates":[95],"method's":[97],"effectiveness":[98],"expanding":[100],"user":[101],"and":[103],"generating":[104],"exploratory":[105],"assist":[108],"refinement.":[110]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
