{"id":"https://openalex.org/W2908500813","doi":"https://doi.org/10.1145/3289600.3291029","title":"A General View for Network Embedding as Matrix Factorization","display_name":"A General View for Network Embedding as Matrix Factorization","publication_year":2019,"publication_date":"2019-01-30","ids":{"openalex":"https://openalex.org/W2908500813","doi":"https://doi.org/10.1145/3289600.3291029","mag":"2908500813"},"language":"en","primary_location":{"id":"doi:10.1145/3289600.3291029","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","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/A5011513741","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0002-2336-7409"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Xin Liu","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076510932","display_name":"Tsuyoshi Murata","orcid":"https://orcid.org/0000-0002-3818-7830"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tsuyoshi Murata","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064163755","display_name":"Kyoung\u2010Sook Kim","orcid":"https://orcid.org/0000-0003-0670-8053"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kyoung-Sook Kim","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080755171","display_name":"Chatchawan Kotarasu","orcid":null},"institutions":[{"id":"https://openalex.org/I25399158","display_name":"Mahidol University","ror":"https://ror.org/01znkr924","country_code":"TH","type":"education","lineage":["https://openalex.org/I25399158"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Chatchawan Kotarasu","raw_affiliation_strings":["Mahidol University, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Mahidol University, Bangkok, Thailand","institution_ids":["https://openalex.org/I25399158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061810614","display_name":"Chenyi Zhuang","orcid":"https://orcid.org/0000-0003-1891-5666"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chenyi Zhuang","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011513741"],"corresponding_institution_ids":["https://openalex.org/I73613424"],"apc_list":null,"apc_paid":null,"fwci":7.6575,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.97752757,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"375","last_page":"383"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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":0.9994000196456909,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9937999844551086,"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/matrix-decomposition","display_name":"Matrix decomposition","score":0.7359321713447571},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.6203624606132507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6133702397346497},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6012305021286011},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5833806991577148},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5477116703987122},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.5128989219665527},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4907747209072113},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.48137858510017395},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.47209829092025757},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4428045153617859},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.43302640318870544},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.41357776522636414},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3734341263771057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33161652088165283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24760860204696655},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.19581863284111023},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18068617582321167}],"concepts":[{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.7359321713447571},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.6203624606132507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6133702397346497},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6012305021286011},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5833806991577148},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5477116703987122},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.5128989219665527},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4907747209072113},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.48137858510017395},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.47209829092025757},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4428045153617859},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.43302640318870544},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.41357776522636414},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3734341263771057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33161652088165283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24760860204696655},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.19581863284111023},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18068617582321167},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3289600.3291029","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:irdb.nii.ac.jp:00897:0004588707","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100795766","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019)","raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W1979104937","https://openalex.org/W1987810983","https://openalex.org/W2001141328","https://openalex.org/W2007444087","https://openalex.org/W2037705937","https://openalex.org/W2037933327","https://openalex.org/W2046253692","https://openalex.org/W2053186076","https://openalex.org/W2062797058","https://openalex.org/W2090891622","https://openalex.org/W2105543219","https://openalex.org/W2117831564","https://openalex.org/W2125031621","https://openalex.org/W2142535891","https://openalex.org/W2145658888","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2168627253","https://openalex.org/W2204756796","https://openalex.org/W2242161203","https://openalex.org/W2315403234","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2415243320","https://openalex.org/W2519887557","https://openalex.org/W2579372251","https://openalex.org/W2583803680","https://openalex.org/W2590351413","https://openalex.org/W2607500032","https://openalex.org/W2612872092","https://openalex.org/W2623187518","https://openalex.org/W2624431344","https://openalex.org/W2739747431","https://openalex.org/W2740934577","https://openalex.org/W2743104969","https://openalex.org/W2744080778","https://openalex.org/W2755092149","https://openalex.org/W2767500585","https://openalex.org/W2767849480","https://openalex.org/W2768092833","https://openalex.org/W2768104274","https://openalex.org/W2768532803","https://openalex.org/W2770250693","https://openalex.org/W2772021946","https://openalex.org/W2787612455","https://openalex.org/W2788338934","https://openalex.org/W2788379054","https://openalex.org/W2788614083","https://openalex.org/W2788792565","https://openalex.org/W2854384722","https://openalex.org/W2883699578","https://openalex.org/W2907373723","https://openalex.org/W2950133940","https://openalex.org/W2962756421","https://openalex.org/W2962779748","https://openalex.org/W2962904108","https://openalex.org/W2962975498","https://openalex.org/W2963169753","https://openalex.org/W2963224980","https://openalex.org/W2963460103","https://openalex.org/W2963512530","https://openalex.org/W2963603080","https://openalex.org/W2963758104","https://openalex.org/W2963885834","https://openalex.org/W2964234429","https://openalex.org/W2999817249","https://openalex.org/W3098702884","https://openalex.org/W3098923689","https://openalex.org/W3103254545","https://openalex.org/W3103995645","https://openalex.org/W3104097132","https://openalex.org/W3104717349","https://openalex.org/W3105705953","https://openalex.org/W4212774754","https://openalex.org/W4291474301","https://openalex.org/W4293651439"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W2037504162","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2539013788","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2075222291","https://openalex.org/W2146544734"],"abstract_inverted_index":{"We":[0,43],"propose":[1],"a":[2,27,33,80,116,148,163],"general":[3,81],"view":[4],"that":[5,19,45,118,143],"demonstrates":[6],"the":[7,21,24,59,64,69,120,125,136],"relationship":[8],"between":[9],"network":[10],"embedding":[11],"approaches":[12,25,161],"and":[13,132,153],"matrix":[14,46,75,144,159],"factorization.":[15],"Unlike":[16],"previous":[17],"works":[18],"present":[20],"equivalence":[22],"for":[23,56,67],"from":[26,37,104],"skip-gram":[28],"model":[29],"perspective,":[30],"we":[31,133],"provide":[32],"more":[34],"fundamental":[35],"connection":[36],"an":[38],"optimization":[39],"(objective":[40],"function)":[41],"perspective.":[42],"demonstrate":[44],"factorization":[47,145,160],"is":[48,55,66,113],"equivalent":[49],"to":[50,76,115,130],"optimizing":[51],"two":[52,121],"objectives:":[53],"one":[54],"bringing":[57],"together":[58],"embeddings":[60,70,127,137],"of":[61,71,86,165],"similar":[62],"nodes;":[63],"other":[65],"separating":[68],"distant":[72],"nodes.":[73],"The":[74,84,109],"be":[77,95],"factorized":[78],"has":[79],"form:":[82],"S-\u03b2.":[83],"elements":[85],"$\\mathbfS":[87],"$":[88],"indicate":[89],"pairwise":[90],"node":[91],"similarities.":[92],"They":[93],"can":[94,134],"based":[96,146],"on":[97,107,147,162],"any":[98],"user-defined":[99],"similarity/distance":[100],"measure":[101,152],"or":[102],"learned":[103],"random":[105],"walks":[106],"networks.":[108,167],"shift":[110],"number":[111],"\u03b2":[112,131],"related":[114],"parameter":[117],"balances":[119],"objectives.":[122],"More":[123],"importantly,":[124],"resulting":[126],"are":[128],"sensitive":[129],"improve":[135],"by":[138],"tuning":[139],"\u03b2.":[140],"Experiments":[141],"show":[142],"new":[149],"proposed":[150],"similarity":[151],"\u03b2-tuning":[154],"strategy":[155],"significantly":[156],"outperforms":[157],"existing":[158],"range":[164],"benchmark":[166]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}