{"id":"https://openalex.org/W3034714178","doi":"https://doi.org/10.24963/ijcai.2020/552","title":"Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding","display_name":"Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3034714178","doi":"https://doi.org/10.24963/ijcai.2020/552","mag":"3034714178"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/552","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015457299","display_name":"Chengkun Zhang","orcid":"https://orcid.org/0000-0002-3188-6583"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Chengkun Zhang","raw_affiliation_strings":["University of Sydney, Australia","Discipline of Business Analytics, The University of Sydney Business School The University of Sydney, Camperdown, NSW 2006, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"Discipline of Business Analytics, The University of Sydney Business School The University of Sydney, Camperdown, NSW 2006, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015817857","display_name":"Junbin Gao","orcid":"https://orcid.org/0000-0001-9803-0256"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junbin Gao","raw_affiliation_strings":["University of Sydney, Australia","Discipline of Business Analytics, The University of Sydney Business School The University of Sydney, Camperdown, NSW 2006, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"Discipline of Business Analytics, The University of Sydney Business School The University of Sydney, Camperdown, NSW 2006, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015457299"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":1.4961,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.86320205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3990","last_page":"3996"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.983299970626831,"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/embedding","display_name":"Embedding","score":0.6362602114677429},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6280574798583984},{"id":"https://openalex.org/keywords/hyperbolic-space","display_name":"Hyperbolic space","score":0.5997806787490845},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5248206257820129},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5101242661476135},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4492468237876892},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4260706603527069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38159894943237305},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35664883255958557},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.2864058315753937},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.092440664768219}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6362602114677429},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6280574798583984},{"id":"https://openalex.org/C83677898","wikidata":"https://www.wikidata.org/wiki/Q1878538","display_name":"Hyperbolic space","level":2,"score":0.5997806787490845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5248206257820129},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5101242661476135},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4492468237876892},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4260706603527069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38159894943237305},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35664883255958557},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.2864058315753937},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.092440664768219},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/552","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1532372219","https://openalex.org/W1832693441","https://openalex.org/W1902027874","https://openalex.org/W1938755728","https://openalex.org/W1971215074","https://openalex.org/W1976645892","https://openalex.org/W2078396547","https://openalex.org/W2104210067","https://openalex.org/W2107425660","https://openalex.org/W2154359981","https://openalex.org/W2157331557","https://openalex.org/W2170240176","https://openalex.org/W2250539671","https://openalex.org/W2252335727","https://openalex.org/W2470673105","https://openalex.org/W2584185835","https://openalex.org/W2605133364","https://openalex.org/W2767210791","https://openalex.org/W2768377508","https://openalex.org/W2804069376","https://openalex.org/W2808310571","https://openalex.org/W2894101493","https://openalex.org/W2951559648","https://openalex.org/W2962918699","https://openalex.org/W2962936818","https://openalex.org/W2962946486","https://openalex.org/W2963360026","https://openalex.org/W2963626623","https://openalex.org/W2963849380","https://openalex.org/W2964046515","https://openalex.org/W2964050265","https://openalex.org/W2964473287","https://openalex.org/W3015754474","https://openalex.org/W3152368098","https://openalex.org/W4292166790","https://openalex.org/W4294238563","https://openalex.org/W4294371460","https://openalex.org/W4295111765","https://openalex.org/W4299279015"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2375873920","https://openalex.org/W2183306018","https://openalex.org/W2146114872","https://openalex.org/W2549990292","https://openalex.org/W2345479200","https://openalex.org/W2392060890","https://openalex.org/W2932872266","https://openalex.org/W4225304485","https://openalex.org/W4308670589"],"abstract_inverted_index":{"Hyperbolic":[0,49],"space":[1,5],"is":[2,102],"a":[3,43],"well-defined":[4],"with":[6,20,98],"constant":[7],"negative":[8],"curvature.":[9],"Recent":[10],"research":[11],"demonstrates":[12],"its":[13,21],"odds":[14],"of":[15,39,58,64,72,114],"capturing":[16],"complex":[17],"hierarchical":[18],"structures":[19],"exceptional":[22],"high":[23],"capacity":[24],"and":[25,61,78,95],"continuous":[26],"tree-like":[27],"properties.":[28],"This":[29],"paper":[30],"bridges":[31],"hyperbolic":[32,44,65,96],"space's":[33],"superiority":[34],"to":[35,104],"the":[36,73,83,112],"power-law":[37],"structure":[38],"documents":[40],"by":[41],"introducing":[42],"neural":[45],"network":[46],"architecture":[47],"named":[48],"Hierarchical":[50],"Attention":[51],"Network":[52],"(Hype-HAN).":[53],"Hype-HAN":[54,101],"defines":[55],"three":[56],"levels":[57],"embeddings":[59],"(word/sentence/document)":[60],"two":[62],"layers":[63],"attention":[66],"mechanism":[67],"(word-to-sentence/sentence-to-document)":[68],"on":[69,82],"Riemannian":[70],"geometries":[71],"Lorentz":[74],"model,":[75],"Klein":[76],"model":[77],"Poincar\u00e9":[79],"model.":[80],"Situated":[81],"evolving":[84],"embedding":[85],"spaces,":[86],"we":[87],"utilize":[88],"both":[89],"conventional":[90],"GRUs":[91,97],"(Gated":[92],"Recurrent":[93],"Units)":[94],"M\u00f6bius":[99],"operations.":[100],"applied":[103],"large":[105],"scale":[106],"datasets.":[107],"The":[108],"empirical":[109],"experiments":[110],"show":[111],"effectiveness":[113],"our":[115],"method.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}