{"id":"https://openalex.org/W7129666508","doi":"https://doi.org/10.48550/arxiv.2602.14335","title":"Predicting New Concept-Object Associations in Astronomy by Mining the Literature","display_name":"Predicting New Concept-Object Associations in Astronomy by Mining the Literature","publication_year":2026,"publication_date":"2026-02-15","ids":{"openalex":"https://openalex.org/W7129666508","doi":"https://doi.org/10.48550/arxiv.2602.14335"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.14335","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126264109","display_name":"Jinchu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Li, Jinchu","raw_affiliation_strings":["Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126174858","display_name":"Yuan-Sen Ting","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting, Yuan-Sen","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070393798","display_name":"Alberto Accomazzi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124175","display_name":"Center for Astrophysics Harvard & Smithsonian","ror":"https://ror.org/03c3r2d17","country_code":"US","type":"education","lineage":["https://openalex.org/I103187081","https://openalex.org/I136199984","https://openalex.org/I4210124175"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Accomazzi, Alberto","raw_affiliation_strings":["The Center for Astrophysics | Harvard & Smithsonian"],"affiliations":[{"raw_affiliation_string":"The Center for Astrophysics | Harvard & Smithsonian","institution_ids":["https://openalex.org/I4210124175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126255896","display_name":"Tirthankar Ghosal","orcid":null},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ghosal, Tirthankar","raw_affiliation_strings":["Oak Ridge National Laboratory"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047358719","display_name":"Nesar Ramachandra","orcid":"https://orcid.org/0000-0001-7772-0346"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramachandra, Nesar","raw_affiliation_strings":["Argonne National Laboratory"],"affiliations":[{"raw_affiliation_string":"Argonne National Laboratory","institution_ids":["https://openalex.org/I1282105669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5126264109"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"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/T12917","display_name":"Astronomy and Astrophysical Research","score":0.10480000078678131,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12917","display_name":"Astronomy and Astrophysical Research","score":0.10480000078678131,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11323","display_name":"Gamma-ray bursts and supernovae","score":0.09350000321865082,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14163","display_name":"Astronomical Observations and Instrumentation","score":0.041099999099969864,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7139000296592712},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6359000205993652},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47699999809265137},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.453000009059906},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.42329999804496765},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.41449999809265137},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.41040000319480896},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4032999873161316}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7139000296592712},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6359000205993652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6243000030517578},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.453000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4318999946117401},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.41449999809265137},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38429999351501465},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C2780977526","wikidata":"https://www.wikidata.org/wiki/Q42417149","display_name":"Data exploration","level":3,"score":0.2818000018596649},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2743000090122223},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.14335","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.14335","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14335","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.14335","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5887041091918945,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,42],"construct":[1],"a":[2,86,157],"concept-object":[3,52],"knowledge":[4],"graph":[5,47],"from":[6,23,64],"the":[7,39,60,104,129],"full":[8],"astro-ph":[9],"corpus":[10],"through":[11],"July":[12],"2025.":[13],"Using":[14],"an":[15,72,92],"automated":[16],"pipeline,":[17],"we":[18,70],"extract":[19],"named":[20],"astrophysical":[21],"objects":[22],"OCR-processed":[24],"papers,":[25],"resolve":[26],"them":[27,33],"to":[28,34,78],"SIMBAD":[29],"identifiers,":[30],"and":[31,66,120,127,135],"link":[32],"scientific":[35],"concepts":[36,61],"annotated":[37],"in":[38,57],"source":[40],"corpus.":[41],"then":[43],"test":[44],"whether":[45],"historical":[46,142],"structure":[48,146],"can":[49],"forecast":[50],"new":[51],"associations":[53],"before":[54],"they":[55],"appear":[56],"print.":[58],"Because":[59],"are":[62],"derived":[63],"clustering":[65],"therefore":[67],"overlap":[68],"semantically,":[69],"apply":[71],"inference-time":[73],"concept-similarity":[74],"smoothing":[75,102],"step":[76],"uniformly":[77],"all":[79],"methods.":[80],"Across":[81],"four":[82],"temporal":[83],"cutoffs":[84],"on":[85,115,122],"physically":[87],"meaningful":[88],"subset":[89],"of":[90],"concepts,":[91],"implicit-feedback":[93],"matrix":[94],"factorization":[95],"model":[96],"(alternating":[97],"least":[98],"squares,":[99],"ALS)":[100],"with":[101],"outperforms":[103],"strongest":[105],"neighborhood":[106,154],"baseline":[107],"(KNN":[108],"using":[109],"text-embedding":[110],"concept":[111],"similarity)":[112],"by":[113,133,149],"16.8%":[114],"NDCG@100":[116],"(0.144":[117],"vs":[118,125],"0.123)":[119],"19.8%":[121],"Recall@100":[123],"(0.175":[124],"0.146),":[126],"exceeds":[128],"best":[130],"recency":[131],"heuristic":[132],"96%":[134],"88%,":[136],"respectively.":[137],"These":[138],"results":[139],"indicate":[140],"that":[141,161],"literature":[143],"encodes":[144],"predictive":[145],"not":[147],"captured":[148],"global":[150],"heuristics":[151],"or":[152],"local":[153],"voting,":[155],"suggesting":[156],"path":[158],"toward":[159],"tools":[160],"could":[162],"help":[163],"triage":[164],"follow-up":[165],"targets":[166],"for":[167],"scarce":[168],"telescope":[169],"time.":[170]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-18T00:00:00"}
