{"id":"https://openalex.org/W2898437625","doi":"https://doi.org/10.1109/asonam.2018.8508579","title":"t-PNE: Tensor-Based Predictable Node Embeddings","display_name":"t-PNE: Tensor-Based Predictable Node Embeddings","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2898437625","doi":"https://doi.org/10.1109/asonam.2018.8508579","mag":"2898437625"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2018.8508579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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/A5065050425","display_name":"Saba A. Al-Sayouri","orcid":"https://orcid.org/0000-0003-1529-7022"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saba A. Al-Sayouri","raw_affiliation_strings":["Systems Science and Industrial Engineering, Binghamton University"],"affiliations":[{"raw_affiliation_string":"Systems Science and Industrial Engineering, Binghamton University","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028367791","display_name":"Ekta Gujral","orcid":"https://orcid.org/0000-0001-7255-3374"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ekta Gujral","raw_affiliation_strings":["Computer Science and Engineering, University of California Riverside"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of California Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015996266","display_name":"Danai Koutra","orcid":"https://orcid.org/0000-0002-3206-8179"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danai Koutra","raw_affiliation_strings":["Computer Science and Engineering, University of California Riverside"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of California Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054849323","display_name":"Evangelos E. Papalexakis","orcid":"https://orcid.org/0000-0002-3411-8483"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Evangelos E. Papalexakis","raw_affiliation_strings":["Computer Science and Engineering, University of California Riverside"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of California Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053471743","display_name":"Sarah S. Lam","orcid":"https://orcid.org/0000-0002-7726-6179"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarah S. Lam","raw_affiliation_strings":["Systems Science and Industrial Engineering, Binghamton University"],"affiliations":[{"raw_affiliation_string":"Systems Science and Industrial Engineering, Binghamton University","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065050425"],"corresponding_institution_ids":["https://openalex.org/I123946342"],"apc_list":null,"apc_paid":null,"fwci":0.1629,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59729378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"491","last_page":"494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9993000030517578,"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":0.9993000030517578,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.8172378540039062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6248679757118225},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6033463478088379},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.5902956128120422},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5815665125846863},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.498673677444458},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4841206967830658},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47926685214042664},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.433709055185318},{"id":"https://openalex.org/keywords/vector-space","display_name":"Vector space","score":0.4198992848396301},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37029722332954407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30790382623672485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30100318789482117},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.11044836044311523}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.8172378540039062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6248679757118225},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6033463478088379},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.5902956128120422},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5815665125846863},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.498673677444458},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4841206967830658},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47926685214042664},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.433709055185318},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.4198992848396301},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37029722332954407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30790382623672485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30100318789482117},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.11044836044311523},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asonam.2018.8508579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1790954942","https://openalex.org/W1888005072","https://openalex.org/W1906783320","https://openalex.org/W1908728294","https://openalex.org/W2000215628","https://openalex.org/W2088252378","https://openalex.org/W2138399168","https://openalex.org/W2154851992","https://openalex.org/W2177614019","https://openalex.org/W2242161203","https://openalex.org/W2387282348","https://openalex.org/W2529121416","https://openalex.org/W2612872092","https://openalex.org/W2621677039","https://openalex.org/W2771685360","https://openalex.org/W2962756421","https://openalex.org/W2963460103","https://openalex.org/W3100330855","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W3215782356","https://openalex.org/W4244478947","https://openalex.org/W4293651439","https://openalex.org/W6639839111","https://openalex.org/W6639917875","https://openalex.org/W6690230747","https://openalex.org/W6744557953","https://openalex.org/W6973773678"],"related_works":["https://openalex.org/W4213150077","https://openalex.org/W2369410163","https://openalex.org/W2059018062","https://openalex.org/W2604585036","https://openalex.org/W2078477160","https://openalex.org/W1989103179","https://openalex.org/W1991172810","https://openalex.org/W125803343","https://openalex.org/W2153421018","https://openalex.org/W2117632582"],"abstract_inverted_index":{"Graph":[0],"representations":[1,60],"have":[2],"increasingly":[3],"grown":[4],"in":[5,22,34,153],"popularity":[6],"during":[7],"the":[8,76,86,90,102,111,114,126],"last":[9],"years.":[10],"Existing":[11],"embedding":[12],"approaches":[13],"explicitly":[14],"encode":[15],"network":[16],"structure.":[17],"Despite":[18],"their":[19],"good":[20],"performance":[21],"downstream":[23],"processes":[24],"(e.g.,":[25],"node":[26,59,87,99],"classification),":[27],"there":[28],"is":[29,89,125],"still":[30],"room":[31],"for":[32],"improvement":[33],"different":[35],"aspects,":[36],"like":[37],"effectiveness.":[38],"In":[39],"this":[40,49],"paper,":[41],"we":[42],"propose,":[43],"t-PNE,":[44],"a":[45,69,80,118,121],"method":[46],"that":[47,110,139],"addresses":[48],"limitation.":[50],"Contrary":[51],"to":[52,94,120,128,147,151],"baseline":[53,143],"methods,":[54],"which":[55],"generally":[56],"learn":[57,95,129],"explicit":[58,96,115],"by":[61,145],"solely":[62],"using":[63,101],"an":[64],"adjacency":[65,73],"matrix,":[66],"t-PNE":[67,140],"avails":[68],"multi-view":[70],"information":[71],"graph-the":[72],"matrix":[74],"represents":[75],"first":[77],"view,":[78],"and":[79,97,113,132],"nearest":[81],"neighbor":[82],"adjacency,":[83],"computed":[84],"over":[85],"features,":[88],"second":[91],"view-in":[92],"order":[93],"implicit":[98,112],"representations,":[100],"Canonical":[103],"Polyadic":[104],"(a.k.a.":[105],"CP)":[106],"decomposition.":[107],"We":[108],"argue":[109],"mapping":[116],"from":[117],"higher-dimensional":[119],"lower-dimensional":[122],"vector":[123],"space":[124],"key":[127],"more":[130],"useful":[131],"highly":[133],"predictable":[134],"representations.":[135],"Extensive":[136],"experiments":[137],"show":[138],"drastically":[141],"outperforms":[142],"methods":[144],"up":[146],"158.6%":[148],"with":[149],"respect":[150],"Micro-Fl,":[152],"several":[154],"multi-label":[155],"classification":[156],"problems.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}