{"id":"https://openalex.org/W4406785346","doi":"https://doi.org/10.48550/arxiv.2501.13252","title":"Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning","display_name":"Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning","publication_year":2025,"publication_date":"2025-01-22","ids":{"openalex":"https://openalex.org/W4406785346","doi":"https://doi.org/10.48550/arxiv.2501.13252"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2501.13252","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.13252","pdf_url":"https://arxiv.org/pdf/2501.13252","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.13252","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107862866","display_name":"Ali Nazari","orcid":"https://orcid.org/0009-0006-4827-802X","observed_orcids":["https://orcid.org/0009-0006-4827-802X"]},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nazari, Ali","raw_affiliation_strings":["Sprott School of Business , Carleton University , Ottawa , ON , Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sprott School of Business , Carleton University , Ottawa , ON , Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055632295","display_name":"Michael Wei\u00df","orcid":"https://orcid.org/0000-0002-8944-389X","observed_orcids":["https://orcid.org/0000-0002-8944-389X"]},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Weiss, Michael","raw_affiliation_strings":["Technology Innovation Management (TIM) program , Carleton University , Ottawa , ON , Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Innovation Management (TIM) program , Carleton University , Ottawa , ON , Canada","institution_ids":["https://openalex.org/I67031392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I67031392"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.5307999849319458,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.5307999849319458,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.4528999924659729,"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/T13204","display_name":"Competitive and Knowledge Intelligence","score":0.006099999882280827,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/topic-modeling","display_name":"topic modeling","score":0.8190000057220459},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.6959999799728394},{"id":"https://openalex.org/keywords/expert-knowledge-integration","display_name":"expert knowledge integration","score":0.7689999938011169},{"id":"https://openalex.org/keywords/topic-selection","display_name":"topic selection","score":0.6209999918937683},{"id":"https://openalex.org/keywords/trend-forecasting","display_name":"trend forecasting","score":0.8330000042915344}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5761069655418396},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.5392237305641174},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36705470085144043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33853721618652344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21611154079437256},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2501.13252","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.13252","pdf_url":"https://arxiv.org/pdf/2501.13252","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2501.13252","doi":"https://doi.org/10.48550/arxiv.2501.13252","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2501.13252","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.13252","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.13252","pdf_url":"https://arxiv.org/pdf/2501.13252","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406785346.pdf","grobid_xml":"https://content.openalex.org/works/W4406785346.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W2015179126","https://openalex.org/W2041404167","https://openalex.org/W2059904123","https://openalex.org/W2082111073","https://openalex.org/W2087712586","https://openalex.org/W2092433168","https://openalex.org/W2115671451","https://openalex.org/W2119652992","https://openalex.org/W2144621682","https://openalex.org/W2145339207","https://openalex.org/W2152161277","https://openalex.org/W2165726932","https://openalex.org/W2168676717","https://openalex.org/W2170353614","https://openalex.org/W2594155836","https://openalex.org/W2601106643","https://openalex.org/W2728092904","https://openalex.org/W2767481062","https://openalex.org/W2782563105","https://openalex.org/W2961152326","https://openalex.org/W2963081964","https://openalex.org/W3000134327","https://openalex.org/W3001721010","https://openalex.org/W3011460647","https://openalex.org/W3016472103","https://openalex.org/W3038067977","https://openalex.org/W3108273660","https://openalex.org/W4247657984","https://openalex.org/W4292289324","https://openalex.org/W4361765877","https://openalex.org/W7118339799"],"related_works":["https://openalex.org/W7124828131","https://openalex.org/W4225725971","https://openalex.org/W2256578089","https://openalex.org/W2998507748","https://openalex.org/W2760331073","https://openalex.org/W4407873231","https://openalex.org/W2752981321","https://openalex.org/W6926229601","https://openalex.org/W4411053507","https://openalex.org/W7127354073"],"abstract_inverted_index":{"In":[0,138],"today's":[1],"rapidly":[2],"evolving":[3,194],"technological":[4,46,195],"landscape,":[5],"organizations":[6,206],"face":[7],"the":[8,43,122,127,139,142,158,174],"challenge":[9],"of":[10,45,126],"integrating":[11],"external":[12],"insights":[13,146],"into":[14],"their":[15],"decision-making":[16],"processes":[17],"to":[18,41,68,81,207],"stay":[19],"competitive.":[20],"To":[21],"address":[22],"this":[23,25],"issue,":[24],"study":[26],"proposes":[27],"a":[28,56,189,200],"method":[29,49],"that":[30,84,183],"combines":[31],"topic":[32,58,75,101,114],"modeling,":[33],"expert":[34,186],"knowledge":[35],"inputs,":[36],"and":[37,66,92,106,124,131,147,180,202],"reinforcement":[38],"learning":[39],"(RL)":[40],"enhance":[42],"detection":[44],"changes.":[47],"The":[48,162],"has":[50],"four":[51],"main":[52],"steps:":[53],"(1)":[54],"Build":[55],"relevant":[57],"model,":[59],"starting":[60],"with":[61,116,185],"textual":[62],"data":[63],"like":[64],"documents":[65],"reports":[67],"find":[69],"key":[70,86],"themes.":[71],"(2)":[72],"Create":[73],"aspect-based":[74],"models.":[76],"Experts":[77],"use":[78,156],"curated":[79],"keywords":[80],"build":[82],"models":[83,108],"showcase":[85],"domain-specific":[87],"aspects.":[88],"(3)":[89],"Iterative":[90],"analysis":[91],"RL":[93],"driven":[94],"refinement:":[95],"We":[96,112],"examine":[97],"metrics":[98],"such":[99],"as":[100],"magnitude,":[102],"similarity,":[103],"entropy":[104],"shifts,":[105],"how":[107],"change":[109],"over":[110],"time.":[111],"optimize":[113],"selection":[115],"RL.":[117],"Our":[118],"reward":[119],"function":[120],"balances":[121],"diversity":[123],"similarity":[125],"topics.":[128],"(4)":[129],"Synthesis":[130],"operational":[132,160],"integration:":[133],"Each":[134],"iteration":[135],"provides":[136],"insights.":[137],"final":[140],"phase,":[141],"experts":[143],"check":[144],"these":[145],"reach":[148],"new":[149],"conclusions.":[150],"These":[151],"conclusions":[152],"are":[153],"designed":[154],"for":[155,192,205],"in":[157,169,177,212],"firm's":[159],"processes.":[161],"application":[163],"is":[164],"tested":[165],"by":[166],"forecasting":[167],"trends":[168,182],"quantum":[170],"communication.":[171],"Results":[172],"demonstrate":[173],"method's":[175],"effectiveness":[176],"identifying,":[178],"ranking,":[179],"tracking":[181],"align":[184],"input,":[187],"providing":[188],"robust":[190],"tool":[191],"exploring":[193],"landscapes.":[196],"This":[197],"research":[198],"offers":[199],"scalable":[201],"adaptive":[203],"solution":[204],"make":[208],"informed":[209],"strategic":[210],"decisions":[211],"dynamic":[213],"environments.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-01-25T00:00:00"}
