{"id":"https://openalex.org/W2794357878","doi":"https://doi.org/10.1109/tnnls.2018.2797060","title":"Tree2Vector: Learning a Vectorial Representation for Tree-Structured Data","display_name":"Tree2Vector: Learning a Vectorial Representation for Tree-Structured Data","publication_year":2018,"publication_date":"2018-02-14","ids":{"openalex":"https://openalex.org/W2794357878","doi":"https://doi.org/10.1109/tnnls.2018.2797060","mag":"2794357878","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994643"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2018.2797060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2797060","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100458457","display_name":"Haijun Zhang","orcid":"https://orcid.org/0000-0002-1648-0227"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haijun Zhang","raw_affiliation_strings":["Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1648-0227","affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715183","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0002-2498-4740"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Wang","raw_affiliation_strings":["Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2498-4740","affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101453596","display_name":"Xiaofei Xu","orcid":"https://orcid.org/0000-0002-9492-0312"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Xu","raw_affiliation_strings":["Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050716572","display_name":"Tommy W. S. Chow","orcid":"https://orcid.org/0000-0001-7051-0434"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tommy W. S. Chow","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7051-0434","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100731724","display_name":"Q. M. Jonathan Wu","orcid":"https://orcid.org/0000-0002-5208-7975"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Q. M. Jonathan Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5208-7975","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada","institution_ids":["https://openalex.org/I74413500"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.7983,"has_fulltext":false,"cited_by_count":101,"citation_normalized_percentile":{"value":0.98324271,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"29","issue":"11","first_page":"5304","last_page":"5318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7055585980415344},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6805056929588318},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.6156842112541199},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5934277176856995},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5749987363815308},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5613571405410767},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5553843379020691},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5480893850326538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5127519369125366},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4958406388759613},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4818347692489624},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.43934985995292664},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37022876739501953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36152148246765137},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3379806876182556},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.325803279876709},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.2548067271709442}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7055585980415344},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6805056929588318},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.6156842112541199},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5934277176856995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5749987363815308},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5613571405410767},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5553843379020691},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5480893850326538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5127519369125366},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4958406388759613},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4818347692489624},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.43934985995292664},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37022876739501953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36152148246765137},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3379806876182556},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.325803279876709},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.2548067271709442},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2018.2797060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2797060","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:29994643","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994643","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G2919415944","display_name":"\u6811\u5f62\u5b50\u56fe\u7684\u7edf\u4e00\u5411\u91cf\u8868\u793a\u53ca\u5176\u591a\u7c7b\u6807\u5206\u7c7b\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61572156","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":65,"referenced_works":["https://openalex.org/W1612003148","https://openalex.org/W1614298861","https://openalex.org/W1653696204","https://openalex.org/W1875120328","https://openalex.org/W1880262756","https://openalex.org/W1956559956","https://openalex.org/W1976373002","https://openalex.org/W1990843604","https://openalex.org/W1991532786","https://openalex.org/W1991711810","https://openalex.org/W2001123951","https://openalex.org/W2007157631","https://openalex.org/W2018712890","https://openalex.org/W2021469159","https://openalex.org/W2027922120","https://openalex.org/W2030068474","https://openalex.org/W2046953300","https://openalex.org/W2048001624","https://openalex.org/W2063620317","https://openalex.org/W2092057784","https://openalex.org/W2095911429","https://openalex.org/W2097018403","https://openalex.org/W2097551246","https://openalex.org/W2103915252","https://openalex.org/W2104019579","https://openalex.org/W2107412086","https://openalex.org/W2107902126","https://openalex.org/W2109868644","https://openalex.org/W2112447569","https://openalex.org/W2115952565","https://openalex.org/W2116341502","https://openalex.org/W2125914984","https://openalex.org/W2127480961","https://openalex.org/W2127713198","https://openalex.org/W2131081720","https://openalex.org/W2131744502","https://openalex.org/W2139939114","https://openalex.org/W2143505744","https://openalex.org/W2145947562","https://openalex.org/W2146037576","https://openalex.org/W2147152072","https://openalex.org/W2151928840","https://openalex.org/W2154315940","https://openalex.org/W2162915993","https://openalex.org/W2163352848","https://openalex.org/W2164501930","https://openalex.org/W2165411019","https://openalex.org/W2174112393","https://openalex.org/W2187089797","https://openalex.org/W2278713724","https://openalex.org/W2325227998","https://openalex.org/W2518500747","https://openalex.org/W2950577311","https://openalex.org/W4231510805","https://openalex.org/W4232730838","https://openalex.org/W4237222446","https://openalex.org/W4300601563","https://openalex.org/W6636440780","https://openalex.org/W6639471703","https://openalex.org/W6639619044","https://openalex.org/W6674642818","https://openalex.org/W6676727762","https://openalex.org/W6679091061","https://openalex.org/W6679775712","https://openalex.org/W6682149207"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W2180954594","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2052835778","https://openalex.org/W3131016912","https://openalex.org/W2115831357","https://openalex.org/W2033010110","https://openalex.org/W2376211578"],"abstract_inverted_index":{"The":[0,94],"tree":[1],"structure":[2],"is":[3,24,75,86,118,141,166,174],"one":[4],"of":[5,35,43,45,67,112,147,155,192],"the":[6,31,40,46,65,110,113,122,128,144,152,156,169,190,193],"most":[7],"powerful":[8],"structures":[9],"for":[10,17,54,107,137,168,196],"data":[11,20,199],"organization.":[12],"An":[13],"efficient":[14],"learning":[15,145],"framework":[16],"transforming":[18,197],"tree-structured":[19,198],"into":[21,57,101,143,200],"vectorial":[22,149,164],"representations":[23],"presented.":[25],"First,":[26],"in":[27,81,176],"attempting":[28],"to":[29,63,77,88],"uncover":[30],"global":[32],"discriminative":[33],"information":[34],"child":[36],"nodes":[37],"hidden":[38],"at":[39,151],"same":[41],"level":[42,154],"all":[44],"trees,":[47],"a":[48,68,71,79,163],"clustering":[49],"technique":[50],"can":[51],"be":[52,89],"adopted":[53],"allocating":[55],"children":[56],"different":[58],"clusters,":[59],"which":[60,82,104],"are":[61,98,105],"used":[62],"formulate":[64],"components":[66,111],"vector.":[69,114],"Moreover,":[70],"locality-sensitive":[72],"reconstruction":[73,96],"method":[74,173,195],"introduced":[76],"model":[78],"process,":[80],"each":[83,138],"parent":[84,124,139],"node":[85,125,140],"assumed":[87],"reconstructed":[90],"by":[91,120],"its":[92,132],"children.":[93,133],"resulting":[95],"coefficients":[97],"reversely":[99],"transformed":[100],"complementary":[102],"coefficients,":[103],"utilized":[106],"locally":[108],"weighting":[109],"A":[115],"new":[116,135],"vector":[117,126,130,136],"formulated":[119],"concatenating":[121],"original":[123],"and":[127,182],"learned":[129],"from":[131],"This":[134,158],"inputted":[142],"process":[146,160],"formulating":[148],"representation":[150,165],"upper":[153],"tree.":[157,171],"recursive":[159],"concludes":[161],"when":[162],"achieved":[167],"entire":[170],"Our":[172],"examined":[175],"two":[177],"applications:":[178],"book":[179],"author":[180],"recommendations":[181],"content-based":[183],"image":[184],"retrieval.":[185],"Extensive":[186],"experimental":[187],"results":[188],"demonstrate":[189],"effectiveness":[191],"proposed":[194],"vectors.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":29},{"year":2018,"cited_by_count":13}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}