{"id":"https://openalex.org/W4402810179","doi":"https://doi.org/10.3233/ssw240010","title":"TWIG-I: Embedding-Free Link Prediction and Cross-KG Transfer Learning Using a Small Neural Architecture","display_name":"TWIG-I: Embedding-Free Link Prediction and Cross-KG Transfer Learning Using a Small Neural Architecture","publication_year":2024,"publication_date":"2024-09-11","ids":{"openalex":"https://openalex.org/W4402810179","doi":"https://doi.org/10.3233/ssw240010"},"language":"en","primary_location":{"id":"doi:10.3233/ssw240010","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ssw240010","pdf_url":null,"source":{"id":"https://openalex.org/S4210172742","display_name":"Studies on the semantic web","issn_l":"2215-0870","issn":["2215-0870"],"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":"ebook platform"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies on the Semantic Web","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/ssw240010","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051084370","display_name":"Jeffrey Sardina","orcid":"https://orcid.org/0000-0003-0654-2938"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Jeffrey Sardina","raw_affiliation_strings":["Trinity College Dublin"],"raw_orcid":"https://orcid.org/0000-0003-0654-2938","affiliations":[{"raw_affiliation_string":"Trinity College Dublin","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053805721","display_name":"Alok Debnath","orcid":"https://orcid.org/0000-0002-1270-369X"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Alok Debnath","raw_affiliation_strings":["Trinity College Dublin"],"raw_orcid":"https://orcid.org/0000-0002-1270-369X","affiliations":[{"raw_affiliation_string":"Trinity College Dublin","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079991004","display_name":"John D. Kelleher","orcid":"https://orcid.org/0000-0001-6462-3248"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"John D. Kelleher","raw_affiliation_strings":["Trinity College Dublin"],"raw_orcid":"https://orcid.org/0000-0001-6462-3248","affiliations":[{"raw_affiliation_string":"Trinity College Dublin","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020871962","display_name":"Declan O\u2019Sullivan","orcid":"https://orcid.org/0000-0003-1090-3548"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Declan O\u2019Sullivan","raw_affiliation_strings":["Trinity College Dublin"],"raw_orcid":"https://orcid.org/0000-0003-1090-3548","affiliations":[{"raw_affiliation_string":"Trinity College Dublin","institution_ids":["https://openalex.org/I205274468"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205274468"],"apc_list":null,"apc_paid":null,"fwci":0.6858,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72135922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.5360000133514404,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.5360000133514404,"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/T12676","display_name":"Machine Learning and ELM","score":0.5170999765396118,"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/T12384","display_name":"Customer churn and segmentation","score":0.5131999850273132,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"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/transfer-of-learning","display_name":"Transfer of learning","score":0.66568523645401},{"id":"https://openalex.org/keywords/twig","display_name":"Twig","score":0.6244695782661438},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6104051470756531},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.610014796257019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5293242335319519},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4764407277107239},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4508202373981476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40093994140625},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13938847184181213},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0975620448589325},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07036486268043518},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.04614022374153137},{"id":"https://openalex.org/keywords/traditional-medicine","display_name":"Traditional medicine","score":0.04482543468475342}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.66568523645401},{"id":"https://openalex.org/C2777601135","wikidata":"https://www.wikidata.org/wiki/Q11162356","display_name":"Twig","level":2,"score":0.6244695782661438},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6104051470756531},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.610014796257019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5293242335319519},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4764407277107239},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4508202373981476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40093994140625},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13938847184181213},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0975620448589325},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07036486268043518},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.04614022374153137},{"id":"https://openalex.org/C556039675","wikidata":"https://www.wikidata.org/wiki/Q771035","display_name":"Traditional medicine","level":1,"score":0.04482543468475342},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ssw240010","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ssw240010","pdf_url":null,"source":{"id":"https://openalex.org/S4210172742","display_name":"Studies on the semantic web","issn_l":"2215-0870","issn":["2215-0870"],"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":"ebook platform"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies on the Semantic Web","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/ssw240010","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ssw240010","pdf_url":null,"source":{"id":"https://openalex.org/S4210172742","display_name":"Studies on the semantic web","issn_l":"2215-0870","issn":["2215-0870"],"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":"ebook platform"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies on the Semantic Web","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2256140659","https://openalex.org/W2101478157","https://openalex.org/W2350931051","https://openalex.org/W2068279027","https://openalex.org/W2364147106","https://openalex.org/W1427245496","https://openalex.org/W3154507827","https://openalex.org/W3025341501","https://openalex.org/W3143738664","https://openalex.org/W2150554682"],"abstract_inverted_index":{"Knowledge":[0,26],"Graphs":[1],"(KGs)":[2],"are":[3,171,180],"relational":[4],"knowledge":[5],"bases":[6],"that":[7,90,142,177],"represent":[8,92],"facts":[9,34],"as":[10,200],"a":[11,41,85,96,201],"set":[12],"of":[13,54,63,95,123,191],"labelled":[14,18],"nodes":[15],"and":[16,66,161,208],"the":[17,37,44,93,184,189],"relations":[19],"between":[20],"them.":[21],"Their":[22],"machine":[23],"learning":[24,136,145,199],"counterpart,":[25],"Graph":[27],"Embeddings":[28],"(KGEs),":[29],"learn":[30],"to":[31,112,150,182],"predict":[32],"new":[33,202],"based":[35],"on":[36,60],"data":[38],"contained":[39],"in":[40,98,152,154,188,204],"KG":[42,97],"\u2013":[43,116],"so-called":[45],"link":[46,55,72,87,185,205],"prediction":[47,56,88,186,206],"task.":[48],"To":[49],"date,":[50],"almost":[51],"all":[52],"forms":[53],"for":[57,71,83,134],"KGs":[58],"rely":[59],"some":[61,155],"form":[62],"embedding":[64],"model,":[65],"KGEs":[67],"hold":[68],"state-of-the-art":[69,113],"status":[70],"prediction.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77],"present":[78],"TWIG-I":[79,107,129,147,163,174,194],"(Topologically-Weighted":[80],"Intelligence":[81],"Generation":[82],"Inference),":[84],"novel":[86],"system":[89],"can":[91,130,148],"features":[94,179],"latent":[99],"space":[100],"without":[101,166],"using":[102,143],"node":[103],"or":[104,120],"edge":[105],"embeddings.":[106,192],"shows":[108],"mixed":[109],"performance":[110,153],"relative":[111],"KGE":[114,159],"models":[115,164],"at":[117],"times":[118],"exceeding":[119],"falling":[121],"short":[122],"baseline":[124],"performance.":[125],"However,":[126],"unlike":[127],"KGEs,":[128],"be":[131],"natively":[132],"used":[133],"transfer":[135,144,198],"across":[137],"distinct":[138],"KGs.":[139],"We":[140],"show":[141],"with":[146],"lead":[149],"increases":[151],"cases":[156],"both":[157],"over":[158,162],"baselines":[160],"trained":[165],"finetuning.":[167],"While":[168],"these":[169],"results":[170],"still":[172],"mixed,":[173],"clearly":[175],"demonstrates":[176],"structural":[178],"sufficient":[181],"solve":[183],"task":[187],"absence":[190],"Finally,":[193],"opens":[195],"up":[196],"cross-KG":[197],"direction":[203],"research":[207],"application.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}