{"id":"https://openalex.org/W4415405275","doi":"https://doi.org/10.18293/seke2025-093","title":"Substructure Mining Based on Fact Reflection","display_name":"Substructure Mining Based on Fact Reflection","publication_year":2025,"publication_date":"2025-09-29","ids":{"openalex":"https://openalex.org/W4415405275","doi":"https://doi.org/10.18293/seke2025-093"},"language":null,"primary_location":{"id":"doi:10.18293/seke2025-093","is_oa":true,"landing_page_url":"https://doi.org/10.18293/seke2025-093","pdf_url":"https://doi.org/10.18293/seke2025-093","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.18293/seke2025-093","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100674036","display_name":"Xinzhi Wang","orcid":"https://orcid.org/0000-0002-9106-2615"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xinzhi Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101652593","display_name":"Zhennan Li","orcid":"https://orcid.org/0000-0002-0230-5719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhennan Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101477114","display_name":"Zhang Yi-ming","orcid":"https://orcid.org/0009-0001-9484-9149"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yiming Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027613327","display_name":"Jiayan Qian","orcid":"https://orcid.org/0000-0002-4228-0771"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiayan Qian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100852232","display_name":"Yinghua Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yinghua Ma","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100674036"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32224361,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2025","issue":null,"first_page":"50","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9125000238418579,"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/substructure","display_name":"Substructure","score":0.5045999884605408},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4787999987602234},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45329999923706055},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43220001459121704},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.41609999537467957},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3953999876976013},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.34310001134872437},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.33899998664855957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6823999881744385},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5274999737739563},{"id":"https://openalex.org/C99679407","wikidata":"https://www.wikidata.org/wiki/Q56761637","display_name":"Substructure","level":2,"score":0.5045999884605408},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45329999923706055},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4172999858856201},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.41609999537467957},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3278999924659729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28850001096725464},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18293/seke2025-093","is_oa":true,"landing_page_url":"https://doi.org/10.18293/seke2025-093","pdf_url":"https://doi.org/10.18293/seke2025-093","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18293/seke2025-093","is_oa":true,"landing_page_url":"https://doi.org/10.18293/seke2025-093","pdf_url":"https://doi.org/10.18293/seke2025-093","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1863638437","display_name":null,"funder_award_id":"23ZR1423100","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7315847417","display_name":null,"funder_award_id":"72204155","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415405275.pdf","grobid_xml":"https://content.openalex.org/works/W4415405275.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Substructure":[0],"mining":[1,61],"serves":[2],"as":[3],"a":[4,47,109],"fundamental":[5],"technique":[6],"for":[7],"uncovering":[8],"key":[9],"patterns":[10,123],"and":[11,23,32,66,85,100,120,159,161],"latent":[12],"risk":[13],"within":[14],"complex":[15],"networks.Existing":[16],"methods":[17,171],"focus":[18],"on":[19,53,125,146,154],"modeling":[20,65],"of":[21,92,179],"topological":[22],"semantic":[24,30,64,78,94,107],"information,":[25],"while":[26],"neglecting":[27],"the":[28,72,90,102,147],"cross-layer":[29,93],"confusion":[31],"initial":[33],"decisions":[34],"unreliability":[35],"resulting":[36],"from":[37],"intrinsic":[38],"coupling":[39],"between":[40,149],"them.Faced":[41],"with":[42],"that,":[43],"this":[44],"study":[45],"proposes":[46],"novel":[48],"Graph":[49],"Transformer":[50],"model":[51],"based":[52,124,145],"fact":[54,119],"reflection,":[55],"named":[56],"RAGphormer,":[57],"which":[58,75,116,141],"enhances":[59],"substructure":[60,118],"through":[62],"high-order":[63],"dynamic":[67,110,131],"decision":[68,111],"reflection.Specifically,":[69],"we":[70],"introduce":[71],"Sub2Token":[73],"module,":[74],"constructs":[76,117],"hierarchical":[77],"encoding":[79],"sequences":[80],"by":[81,105],"integrating":[82],"node-level,":[83],"substructure-level,":[84],"multi-hop":[86,97,106],"neighborhood":[87,98],"features.It":[88],"overcomes":[89],"limitations":[91],"sharing":[95],"among":[96],"nodes,":[99],"mitigates":[101],"noise":[103],"caused":[104],"entanglement.Furthermore,":[108],"reflection":[112],"mechanism":[113],"is":[114,134],"proposed,":[115],"counterfactual":[121],"feature":[122,151],"an":[126,177],"adaptive":[127],"KMeans":[128],"clustering":[129],"algorithm.A":[130],"thresholding":[132],"strategy":[133],"employed":[135],"to":[136,181],"identify":[137],"potentially":[138],"unreliable":[139],"predictions,":[140],"are":[142],"then":[143],"revised":[144],"discrepancies":[148],"corresponding":[150],"patterns.Extensive":[152],"experiments":[153],"two":[155],"private":[156],"datasets":[157],"(ChTech":[158],"EnTech)":[160],"one":[162],"public":[163],"dataset":[164],"(Cora)":[165],"demonstrate":[166],"that":[167],"RAGphormer":[168],"outperforms":[169],"baseline":[170],"across":[172],"multiple":[173],"evaluation":[174],"metrics,":[175],"achieving":[176],"accuracy":[178],"up":[180],"98.8%.":[182]},"counts_by_year":[],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2025-10-22T00:00:00"}