{"id":"https://openalex.org/W4396843701","doi":"https://doi.org/10.1145/3589335.3651565","title":"Tackling Long-Tail Entities for Temporal Knowledge Graph Completion","display_name":"Tackling Long-Tail Entities for Temporal Knowledge Graph Completion","publication_year":2024,"publication_date":"2024-05-12","ids":{"openalex":"https://openalex.org/W4396843701","doi":"https://doi.org/10.1145/3589335.3651565"},"language":"en","primary_location":{"id":"doi:10.1145/3589335.3651565","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651565","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651565","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651565","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085886529","display_name":"Mehrnoosh Mirtaheri","orcid":"https://orcid.org/0000-0002-3276-7412"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mehrnoosh Mirtaheri","raw_affiliation_strings":["USC Information Sciences Institute, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"USC Information Sciences Institute, Los Angeles, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009957887","display_name":"Ryan A. Rossi","orcid":"https://orcid.org/0000-0001-9758-0635"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan A. Rossi","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100718934","display_name":"Sungchul Kim","orcid":"https://orcid.org/0000-0003-3580-5290"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sungchul Kim","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073589054","display_name":"Kanak Mahadik","orcid":"https://orcid.org/0000-0002-6780-4199"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kanak Mahadik","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767817","display_name":"Tong Yu","orcid":"https://orcid.org/0000-0002-1819-5614"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tong Yu","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102715768","display_name":"Xiang Chen","orcid":"https://orcid.org/0009-0009-9864-355X"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Chen","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040786186","display_name":"Mohammad Rostami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammad Rostami","raw_affiliation_strings":["USC Information Sciences Institute, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"USC Information Sciences Institute, Los Angeles, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5085886529"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0851,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88362521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"497","last_page":"500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9912999868392944,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9912999868392944,"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/computer-science","display_name":"Computer science","score":0.7322088479995728},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5936810374259949},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4712170660495758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3380105495452881},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2857060432434082}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7322088479995728},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5936810374259949},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4712170660495758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3380105495452881},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2857060432434082}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589335.3651565","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651565","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651565","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589335.3651565","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651565","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651565","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396843701.pdf"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2006149654","https://openalex.org/W2798864014","https://openalex.org/W2890410208","https://openalex.org/W3006180822","https://openalex.org/W3097986917","https://openalex.org/W3101611558","https://openalex.org/W3175405178","https://openalex.org/W3182741322","https://openalex.org/W6603374586"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W2054026175"],"abstract_inverted_index":{"Most":[0],"Temporal":[1],"Knowledge":[2],"Graphs":[3],"(TKGs)":[4],"exhibit":[5],"a":[6,39,61,89,98,131,140],"long-tail":[7,125],"entity":[8,66],"distribution,":[9],"where":[10],"the":[11,69,95],"majority":[12],"of":[13,65,71,100],"entities":[14,28],"have":[15],"sparse":[16],"connections.":[17,33],"Existing":[18],"TKG":[19,50,96],"completion":[20,51],"methods":[21,114],"struggle":[22],"with":[23,47],"managing":[24],"new":[25],"or":[26],"unseen":[27],"that":[29,43,93,109],"often":[30],"lack":[31],"sufficient":[32],"In":[34],"this":[35],"paper,":[36],"we":[37,84],"introduce":[38],"model-agnostic":[40],"enhancement":[41,58],"layer":[42,59],"can":[44],"be":[45],"integrated":[46],"any":[48],"existing":[49,113],"method":[52],"to":[53],"improve":[54],"its":[55],"performance.":[56],"This":[57],"employs":[60],"broader,":[62],"global":[63],"definition":[64],"similarity,":[67],"transcending":[68],"limitations":[70],"local":[72],"neighborhood":[73],"proximity":[74],"found":[75],"in":[76,88,115,123,134],"Graph":[77],"Neural":[78],"Network":[79],"(GNN)":[80],"based":[81],"methods.":[82],"Additionally,":[83],"conduct":[85],"our":[86,110,128],"evaluations":[87],"novel,":[90],"realistic":[91],"setup":[92],"treats":[94],"as":[97],"stream":[99],"evolving":[101],"data.":[102],"Evaluations":[103],"on":[104,136,143],"two":[105],"benchmark":[106],"datasets":[107],"demonstrate":[108],"framework":[111],"surpasses":[112],"overall":[116],"link":[117,120],"prediction,":[118,121],"inductive":[119],"and":[122,139],"addressing":[124],"entities.":[126],"Notably,":[127],"approach":[129],"achieves":[130],"10%":[132],"improvement":[133],"MRR":[135],"one":[137],"dataset":[138],"15%":[141],"increase":[142],"another.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}