{"id":"https://openalex.org/W2997631794","doi":"https://doi.org/10.1145/3336191.3371781","title":"Initialization for Network Embedding","display_name":"Initialization for Network Embedding","publication_year":2020,"publication_date":"2020-01-20","ids":{"openalex":"https://openalex.org/W2997631794","doi":"https://doi.org/10.1145/3336191.3371781","mag":"2997631794"},"language":"en","primary_location":{"id":"doi:10.1145/3336191.3371781","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th 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/A5073960312","display_name":"Wenqing Lin","orcid":"https://orcid.org/0000-0003-4741-801X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenqing Lin","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081247449","display_name":"Feng He","orcid":"https://orcid.org/0000-0001-5128-3061"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng He","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086137381","display_name":"Faqiang Zhang","orcid":"https://orcid.org/0000-0001-5502-6644"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Faqiang Zhang","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101449143","display_name":"Xu Cheng","orcid":"https://orcid.org/0000-0002-5375-7096"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Cheng","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101912243","display_name":"Hongyun Cai","orcid":"https://orcid.org/0000-0001-5853-2841"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyun Cai","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073960312"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":1.0605,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.81417617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"367","last_page":"374"},"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":0.9954000115394592,"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/initialization","display_name":"Initialization","score":0.9176552295684814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7840899229049683},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6853504776954651},{"id":"https://openalex.org/keywords/graph-partition","display_name":"Graph partition","score":0.6692354679107666},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5843932628631592},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5580372214317322},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.551277220249176},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.5473759174346924},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5279490351676941},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5249892473220825},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.419574111700058},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3528152108192444},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32728394865989685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13450458645820618},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07233905792236328}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.9176552295684814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7840899229049683},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6853504776954651},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.6692354679107666},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5843932628631592},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5580372214317322},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.551277220249176},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.5473759174346924},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5279490351676941},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5249892473220825},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.419574111700058},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3528152108192444},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32728394865989685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13450458645820618},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07233905792236328},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3336191.3371781","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","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":24,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W1910515323","https://openalex.org/W2090891622","https://openalex.org/W2116940697","https://openalex.org/W2118966355","https://openalex.org/W2131571251","https://openalex.org/W2153752762","https://openalex.org/W2154851992","https://openalex.org/W2178237821","https://openalex.org/W2393319904","https://openalex.org/W2469279958","https://openalex.org/W2600077159","https://openalex.org/W2612872092","https://openalex.org/W2759045585","https://openalex.org/W2768352146","https://openalex.org/W2787612455","https://openalex.org/W2888221391","https://openalex.org/W2962756421","https://openalex.org/W2963512530","https://openalex.org/W3009233884","https://openalex.org/W3103995645","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4291474301"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W2015634066","https://openalex.org/W2048339306","https://openalex.org/W2028295504","https://openalex.org/W3046629113","https://openalex.org/W3139829055","https://openalex.org/W2583811263","https://openalex.org/W3211941742","https://openalex.org/W2035944803","https://openalex.org/W2981547104"],"abstract_inverted_index":{"Network":[0],"embedding":[1,63,110,121,138],"has":[2],"been":[3],"intensively":[4],"studied":[5],"in":[6,12,44,114,142],"the":[7,27,39,45,68,71,82,88,102,106,109,115,119,123,131,137,140,143,160,163,167,186,191,195],"literature":[8],"and":[9,19,76,94,134,172,179],"widely":[10],"used":[11],"various":[13,36,150],"applications,":[14],"such":[15],"as":[16],"link":[17,170],"prediction":[18,171],"node":[20,113,173],"classification.":[21],"While":[22],"previous":[23],"work":[24],"focus":[25],"on":[26,73,101,122,149,166],"design":[28],"of":[29,41,59,70,108,162,169,188,194],"new":[30],"algorithms":[31,72,165],"or":[32],"are":[33],"tailored":[34],"for":[35,61,111],"problem":[37],"settings,":[38],"discussion":[40],"initialization":[42,60,107,156,189],"strategies":[43],"learning":[46],"process":[47],"is":[48,127],"often":[49],"missed.":[50],"In":[51],"this":[52,56],"work,":[53],"we":[54,79,152,183],"address":[55],"important":[57],"issue":[58],"network":[62,120],"that":[64,86,154,185],"could":[65],"dramatically":[66],"improve":[67],"performance":[69,161],"both":[74],"effectiveness":[75],"efficiency.":[77],"Specifically,":[78],"first":[80],"exploit":[81],"graph":[83,89,99,116],"partition":[84],"technique":[85,157,187],"divides":[87],"into":[90],"several":[91],"disjoint":[92],"subsets,":[93],"then":[95,135],"construct":[96],"an":[97],"abstract":[98,124],"based":[100],"partitions.":[103],"We":[104],"obtain":[105],"each":[112],"by":[117,175,197],"computing":[118],"graph,":[125,133],"which":[126],"much":[128],"smaller":[129],"than":[130],"input":[132,144],"propagating":[136],"among":[139],"nodes":[141],"graph.":[145],"With":[146],"extensive":[147],"experiments":[148],"datasets,":[151],"demonstrate":[153],"our":[155],"significantly":[158],"improves":[159],"state-of-the-art":[164],"evaluations":[168],"classification":[174],"up":[176],"to":[177],"7.76%":[178],"8.74%":[180],"respectively.":[181],"Besides,":[182],"show":[184],"reduces":[190],"running":[192],"time":[193],"state-of-the-arts":[196],"at":[198],"least":[199],"20%.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}