{"id":"https://openalex.org/W4284698961","doi":"https://doi.org/10.1145/3477495.3531990","title":"HTKG","display_name":"HTKG","publication_year":2022,"publication_date":"2022-07-06","ids":{"openalex":"https://openalex.org/W4284698961","doi":"https://doi.org/10.1145/3477495.3531990"},"language":"en","primary_location":{"id":"doi:10.1145/3477495.3531990","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531990","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5101769560","display_name":"Yuxiang Zhang","orcid":"https://orcid.org/0000-0001-5228-3215"},"institutions":[{"id":"https://openalex.org/I28813325","display_name":"Civil Aviation University of China","ror":"https://ror.org/03je71k37","country_code":"CN","type":"education","lineage":["https://openalex.org/I28813325"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxiang Zhang","raw_affiliation_strings":["Civil Aviation University of China, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Civil Aviation University of China, Tianjin, China","institution_ids":["https://openalex.org/I28813325"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101889270","display_name":"Tao Jiang","orcid":"https://orcid.org/0009-0000-5359-4488"},"institutions":[{"id":"https://openalex.org/I28813325","display_name":"Civil Aviation University of China","ror":"https://ror.org/03je71k37","country_code":"CN","type":"education","lineage":["https://openalex.org/I28813325"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Jiang","raw_affiliation_strings":["Civil Aviation University of China, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Civil Aviation University of China, Tianjin, China","institution_ids":["https://openalex.org/I28813325"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101998583","display_name":"Tianyu Yang","orcid":"https://orcid.org/0000-0001-5645-7059"},"institutions":[{"id":"https://openalex.org/I28813325","display_name":"Civil Aviation University of China","ror":"https://ror.org/03je71k37","country_code":"CN","type":"education","lineage":["https://openalex.org/I28813325"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Yang","raw_affiliation_strings":["Civil Aviation University of China, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Civil Aviation University of China, Tianjin, China","institution_ids":["https://openalex.org/I28813325"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418684","display_name":"Xiaoli Li","orcid":"https://orcid.org/0000-0002-0762-6562"},"institutions":[{"id":"https://openalex.org/I4210161496","display_name":"A*STAR Graduate Academy","ror":"https://ror.org/059yjzn93","country_code":"SG","type":"education","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210161496"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaoli Li","raw_affiliation_strings":["A*STAR, Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"A*STAR, Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I4210161496"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046924740","display_name":"Suge Wang","orcid":"https://orcid.org/0000-0002-1553-2937"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suge Wang","raw_affiliation_strings":["Shanxi University, Taiyuan, China"],"affiliations":[{"raw_affiliation_string":"Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101769560"],"corresponding_institution_ids":["https://openalex.org/I28813325"],"apc_list":null,"apc_paid":null,"fwci":1.3512,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.82676147,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1044","last_page":"1054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":1.0,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":1.0,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9465000033378601,"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/computer-science","display_name":"Computer science","score":0.8677291870117188},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7571864724159241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6451404094696045},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5829638838768005},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5468180179595947},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5341894030570984},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5214682817459106},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4989786148071289},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.49335089325904846},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.47862452268600464},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37094390392303467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.340098112821579},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.176744282245636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8677291870117188},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7571864724159241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6451404094696045},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5829638838768005},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5468180179595947},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5341894030570984},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5214682817459106},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4989786148071289},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.49335089325904846},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.47862452268600464},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37094390392303467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.340098112821579},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.176744282245636},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477495.3531990","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531990","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6899999976158142}],"awards":[{"id":"https://openalex.org/G8938089882","display_name":null,"funder_award_id":"U1933114,62076158","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1490343430","https://openalex.org/W1880262756","https://openalex.org/W1973137995","https://openalex.org/W2003899488","https://openalex.org/W2005564522","https://openalex.org/W2030903088","https://openalex.org/W2045181608","https://openalex.org/W2129557600","https://openalex.org/W2132827946","https://openalex.org/W2136075087","https://openalex.org/W2144148101","https://openalex.org/W2145049651","https://openalex.org/W2150286230","https://openalex.org/W2152321560","https://openalex.org/W2157331557","https://openalex.org/W2167329753","https://openalex.org/W2566297247","https://openalex.org/W2604912255","https://openalex.org/W2740811004","https://openalex.org/W2742094278","https://openalex.org/W2767253343","https://openalex.org/W2767322471","https://openalex.org/W2783786042","https://openalex.org/W2792059528","https://openalex.org/W2888766462","https://openalex.org/W2914076857","https://openalex.org/W2932847124","https://openalex.org/W2949647400","https://openalex.org/W2949877232","https://openalex.org/W2949963192","https://openalex.org/W2962974924","https://openalex.org/W2963223306","https://openalex.org/W2963245897","https://openalex.org/W2963265326","https://openalex.org/W2963269843","https://openalex.org/W2963275829","https://openalex.org/W2963411289","https://openalex.org/W2963506530","https://openalex.org/W2963531963","https://openalex.org/W2973226110","https://openalex.org/W3022187094","https://openalex.org/W3034379969","https://openalex.org/W3034735823","https://openalex.org/W3035328829","https://openalex.org/W3113450614","https://openalex.org/W3153071038","https://openalex.org/W3156614760","https://openalex.org/W3159075545","https://openalex.org/W3173180518","https://openalex.org/W3173799534","https://openalex.org/W3177067286","https://openalex.org/W3199768079","https://openalex.org/W3211683577","https://openalex.org/W4288280762"],"related_works":["https://openalex.org/W1496222301","https://openalex.org/W3207760230","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W2996014667","https://openalex.org/W56136284","https://openalex.org/W2415415256","https://openalex.org/W3013878979","https://openalex.org/W3136065093","https://openalex.org/W2566640356"],"abstract_inverted_index":{"Keyphrases":[0],"can":[1],"concisely":[2],"describe":[3],"the":[4,23,32,37,59,64,97,102,138,145,150,167],"high-level":[5],"topics":[6],"discussed":[7],"in":[8],"a":[9,42,72,90,108],"document":[10],"that":[11,95,162],"usually":[12],"possesses":[13],"hierarchical":[14,24,38,60,74,92,118,152],"topic":[15,25,39,61,93,99,119,153],"structures.":[16],"Thus,":[17],"it":[18,29],"is":[19,47,144],"crucial":[20],"to":[21,30,56,62,114,128,148,154],"understand":[22],"structures":[26],"and":[27,107],"employ":[28],"guide":[31,155],"keyphrase":[33,44,65,82,111,156],"identification.":[34],"However,":[35],"integrating":[36],"information":[40,133],"into":[41],"deep":[43],"generation":[45,66,79,112],"model":[46,94,113],"unexplored.":[48],"In":[49],"this":[50,143],"paper,":[51],"we":[52,70],"focus":[53],"on":[54],"how":[55],"effectively":[57],"exploit":[58],"improve":[63],"performance":[67],"(HTKG).":[68],"Specifically,":[69],"propose":[71],"novel":[73],"topic-guided":[75],"variational":[76,109],"neural":[77,91,110,151],"sequence":[78],"method":[80,164],"for":[81],"generation,":[83],"which":[84],"consists":[85],"of":[86,105,140],"two":[87,123],"major":[88],"modules:":[89],"learns":[96],"latent":[98],"tree":[100],"across":[101,171],"whole":[103],"corpus":[104],"documents,":[106],"generate":[115],"keyphrases":[116],"under":[117],"guidance.":[120],"Finally,":[121],"these":[122],"modules":[124],"are":[125],"jointly":[126],"trained":[127],"help":[129],"them":[130],"learn":[131],"complementary":[132],"from":[134],"each":[135],"other.":[136],"To":[137],"best":[139],"our":[141,163],"knowledge,":[142],"first":[146],"attempt":[147],"leverage":[149],"generation.":[157],"The":[158],"experimental":[159],"results":[160],"demonstrate":[161],"significantly":[165],"outperforms":[166],"existing":[168],"state-of-the-art":[169],"methods":[170],"five":[172],"benchmark":[173],"datasets.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-07-08T00:00:00"}
