{"id":"https://openalex.org/W7225427586","doi":"https://doi.org/10.5281/zenodo.23996304","title":"Temporal Request-Frequency Prediction for Predictive Computing in Generative AI: Forecasting Future Query Volumes Across Multiple Time Horizons","display_name":"Temporal Request-Frequency Prediction for Predictive Computing in Generative AI: Forecasting Future Query Volumes Across Multiple Time Horizons","publication_year":2026,"publication_date":"2026-11-06","ids":{"openalex":"https://openalex.org/W7225427586","doi":"https://doi.org/10.5281/zenodo.23996304"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23996304","doi":"https://doi.org/10.5281/zenodo.23996304","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23996304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23996304","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100638045","display_name":"Jincheng Zhang","orcid":"https://orcid.org/0000-0001-7332-6704","observed_orcids":["https://orcid.org/0000-0001-7332-6704","https://orcid.org/0009-0005-1860-0009"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Jincheng","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0005-1860-0009","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100638045"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.31929999589920044,"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"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.31929999589920044,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.07259999960660934,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.05490000173449516,"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/generative-ai","display_name":"generative AI","score":0.7990000247955322},{"id":"https://openalex.org/keywords/multi-horizon-forecasting","display_name":"multi-horizon forecasting","score":0.8820000290870667},{"id":"https://openalex.org/keywords/large-language-model-inference","display_name":"large language model inference","score":0.9399999976158142},{"id":"https://openalex.org/keywords/computational-resource-allocation","display_name":"computing resource allocation","score":0.6690000295639038},{"id":"https://openalex.org/keywords/query-classification","display_name":"query classification","score":0.6240000128746033},{"id":"https://openalex.org/keywords/query-clustering","display_name":"query clustering","score":0.5979999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8026000261306763},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5631999969482422},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5569000244140625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4871000051498413},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4343999922275543},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41530001163482666},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C917703","wikidata":"https://www.wikidata.org/wiki/Q7239668","display_name":"Predictive inference","level":5,"score":0.34389999508857727},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3118000030517578},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.25679999589920044},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23996304","doi":"https://doi.org/10.5281/zenodo.23996304","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23996304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"},{"id":"doi:10.5281/zenodo.23996305","doi":"https://doi.org/10.5281/zenodo.23996305","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23996305","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"doi:10.5281/zenodo.23996304","doi":"https://doi.org/10.5281/zenodo.23996304","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23996304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7225267314","https://openalex.org/W7225419693","https://openalex.org/W7225398588","https://openalex.org/W7225385268","https://openalex.org/W7225275234","https://openalex.org/W7225389669","https://openalex.org/W7225419399","https://openalex.org/W7225411818","https://openalex.org/W7225376051","https://openalex.org/W7225401292"],"abstract_inverted_index":{"The":[0,143,276,318],"increasing":[1],"adoption":[2],"of":[3,43,133,246,340],"generative":[4,103,315],"artificial":[5],"intelligence":[6],"has":[7],"created":[8],"substantial":[9],"and":[10,76,130,161,178,188,210,229,244,249,267,337],"continuously":[11],"changing":[12],"computational":[13,36,45,190,231,251,270,294,312,342],"demand":[14,49,163,174],"for":[15,102,310,324],"large":[16],"language":[17],"model":[18],"(LLM)":[19],"inference":[20,24],"services.":[21],"Although":[22],"existing":[23],"optimization":[25],"approaches":[26],"primarily":[27,115],"respond":[28],"to":[29,97,165,197,258],"incoming":[30],"requests":[31,135],"or":[32,140,288],"reuse":[33],"previously":[34],"generated":[35],"results,":[37],"predictive":[38,53],"computing":[39],"introduces":[40,88],"the":[41,64,127,219,241,268,299,335],"possibility":[42],"preparing":[44],"resources":[46,313],"before":[47],"actual":[48],"materializes.":[50],"However,":[51],"effective":[52],"computation":[54],"requires":[55,68],"more":[56],"than":[57],"identifying":[58],"which":[59,114,302],"questions":[60,139],"may":[61],"appear":[62],"in":[63,314],"future.":[65],"It":[66],"also":[67],"estimating":[69,126],"how":[70,234],"frequently":[71],"different":[72,215],"questions,":[73],"query":[74,141,176,237],"categories,":[75],"information":[77,154,309,330],"topics":[78],"will":[79,121],"be":[80],"requested":[81],"across":[82,106,214],"future":[83,99,119,134,199,236,282,329,341],"time":[84,216],"intervals.":[85,217],"This":[86],"paper":[87,220],"Temporal":[89],"Request-Frequency":[90],"Prediction":[91],"(TRFP),":[92],"a":[93,118,222],"forecasting":[94,212,260,291,334],"framework":[95,145,277],"designed":[96],"estimate":[98,198],"request":[100,120,148,200,203,208,227,283],"volumes":[101,238],"AI":[104,316,326],"services":[105],"multiple":[107],"temporal":[108,131,150,173,262,338],"horizons.":[109],"Unlike":[110],"binary":[111],"query-occurrence":[112],"prediction,":[113,182],"estimates":[116],"whether":[117],"appear,":[122],"TRFP":[123],"focuses":[124],"on":[125],"expected":[128,207],"number":[129],"distribution":[132,339],"associated":[136],"with":[137],"particular":[138],"categories.":[142],"proposed":[144,257,319],"integrates":[146],"historical":[147],"statistics,":[149],"behavioral":[151],"patterns,":[152],"emerging":[153],"trends,":[155],"external":[156],"event":[157],"signals,":[158],"query-category":[159],"representations,":[160],"short-term":[162],"fluctuations":[164],"generate":[166],"multi-horizon":[167,180,303],"request-frequency":[168,304],"forecasts.":[169],"Its":[170],"architecture":[171],"incorporates":[172],"representation,":[175],"classification":[177],"clustering,":[179],"request-count":[181],"probabilistic":[183],"uncertainty":[184],"estimation,":[185],"prediction":[186,264,305],"updating,":[187],"forecasting-aware":[189],"planning.":[191],"A":[192],"mathematical":[193],"formulation":[194],"is":[195,256],"developed":[196],"counts,":[201],"distinguish":[202],"occurrence":[204],"probability":[205],"from":[206,327],"frequency,":[209],"quantify":[211],"errors":[213],"Furthermore,":[218],"establishes":[221],"theoretical":[223],"connection":[224],"between":[225],"predicted":[226],"frequency":[228],"proactive":[230],"preparation,":[232],"demonstrating":[233],"estimated":[235],"can":[239,306],"inform":[240],"selection,":[242],"prioritization,":[243],"scheduling":[245],"advance-generated":[247],"responses":[248],"reusable":[250],"resources.":[252],"An":[253],"experimental":[254],"methodology":[255],"evaluate":[259],"accuracy,":[261],"consistency,":[263],"lead":[265],"time,":[266],"resulting":[269],"implications":[271],"under":[272,301],"chronological":[273],"testing":[274],"conditions.":[275],"does":[278],"not":[279],"assume":[280],"that":[281,289],"frequencies":[284],"are":[285],"perfectly":[286],"predictable":[287],"accurate":[290],"necessarily":[292],"guarantees":[293],"savings.":[295],"Instead,":[296],"it":[297],"investigates":[298],"conditions":[300],"provide":[307],"useful":[308],"allocating":[311],"systems.":[317],"research":[320],"extends":[321],"Predictive":[322],"Computing":[323],"Generative":[325],"anticipating":[328],"requirements":[331],"toward":[332],"quantitatively":[333],"intensity":[336],"demand.":[343]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}
