{"id":"https://openalex.org/W7169578257","doi":"https://doi.org/10.48550/arxiv.2607.14102","title":"UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure","display_name":"UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure","publication_year":2026,"publication_date":"2026-05-06","ids":{"openalex":"https://openalex.org/W7169578257","doi":"https://doi.org/10.48550/arxiv.2607.14102"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.14102","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.14102","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,"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.14102","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089081657","display_name":"Taoran Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Taoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141056077","display_name":"Yan Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141076614","display_name":"Chunping Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chunping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141069497","display_name":"Yang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141071860","display_name":"Lei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5141093199","display_name":"Yang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11719","display_name":"Data Quality and Management","score":0.24940000474452972,"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"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.24940000474452972,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.17479999363422394,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.15150000154972076,"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/process","display_name":"Process (computing)","score":0.5320000052452087},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4666999876499176},{"id":"https://openalex.org/keywords/unified-model","display_name":"Unified Model","score":0.40310001373291016},{"id":"https://openalex.org/keywords/dynamic-data","display_name":"Dynamic data","score":0.38769999146461487},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.38519999384880066},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.37720000743865967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131999969482422},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5320000052452087},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43799999356269836},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4027000069618225},{"id":"https://openalex.org/C197298091","wikidata":"https://www.wikidata.org/wiki/Q5318963","display_name":"Dynamic data","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C97686452","wikidata":"https://www.wikidata.org/wiki/Q7604153","display_name":"Static analysis","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34380000829696655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3328000009059906},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.14102","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.14102","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,"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.14102","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.14102","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,"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.41092193126678467,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1],"rapid":[2],"growth":[3],"of":[4,146,173],"digital":[5],"data,":[6],"real-world":[7,159],"applications":[8],"increasingly":[9],"involve":[10],"hierarchical":[11,84],"information":[12],"that":[13,82,102,164],"combines":[14],"static":[15,50,72,105,126],"attributes":[16,53,129],"with":[17,70],"dynamic":[18,52,74,108,128],"records.":[19],"Modeling":[20],"such":[21],"heterogeneous":[22],"data":[23,45,69,142],"in":[24,54,88],"a":[25,64,78,89,111,131,158],"unified":[26,65,90,118],"and":[27,47,51,73,85,107,127,144,157],"generalizable":[28],"manner":[29],"remains":[30],"challenging.":[31],"Existing":[32],"approaches":[33],"often":[34],"rely":[35],"on":[36,116,153,176],"extensive":[37],"manual":[38],"design,":[39],"are":[40],"tightly":[41],"coupled":[42],"to":[43,140],"specific":[44],"schemas,":[46,143],"typically":[48],"process":[49],"isolation,":[55],"thereby":[56],"overlooking":[57],"their":[58],"implicit":[59],"interactions.":[60],"We":[61],"propose":[62],"UniSAGE,":[63],"framework":[66],"for":[67],"modeling":[68],"both":[71],"attributes.":[75],"UniSAGE":[76,120,135,165],"constructs":[77],"global":[79],"attribute":[80],"graph":[81],"represents":[83],"temporal":[86],"relationships":[87],"structure.":[91],"To":[92],"ensure":[93],"representational":[94],"consistency,":[95],"it":[96],"introduces":[97],"two":[98],"orthogonal":[99],"parameter":[100],"subspaces":[101],"jointly":[103],"support":[104],"aggregation":[106],"reasoning":[109],"within":[110],"shared":[112],"semantic":[113],"space.":[114],"Building":[115],"these":[117],"representations,":[119],"further":[121],"enables":[122],"task-specific":[123],"interaction":[124],"between":[125],"via":[130],"lightweight":[132],"hyper-structure":[133],"mechanism.":[134],"is":[136],"fully":[137],"automated,":[138],"robust":[139],"evolving":[141],"capable":[145],"capturing":[147],"complex":[148],"cross-attribute":[149],"dependencies.":[150],"Extensive":[151],"experiments":[152],"multiple":[154],"public":[155],"benchmarks":[156],"financial":[160],"behavior":[161],"dataset":[162],"demonstrate":[163],"consistently":[166],"outperforms":[167],"existing":[168],"methods,":[169],"achieving":[170],"performance":[171],"improvements":[172],"over":[174],"10%":[175],"several":[177],"tasks.":[178]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-18T00:00:00"}
