{"id":"https://openalex.org/W2999122980","doi":"https://doi.org/10.1145/3341161.3345643","title":"A hierarchical insurance recommendation framework using GraphOLAM approach","display_name":"A hierarchical insurance recommendation framework using GraphOLAM approach","publication_year":2019,"publication_date":"2019-08-27","ids":{"openalex":"https://openalex.org/W2999122980","doi":"https://doi.org/10.1145/3341161.3345643","mag":"2999122980"},"language":"en","primary_location":{"id":"doi:10.1145/3341161.3345643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341161.3345643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and 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/A5109339790","display_name":"Sirui Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sirui Sun","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043114890","display_name":"Bin Wu","orcid":"https://orcid.org/0000-0001-5787-9536"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036056631","display_name":"Zixing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixing Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025534588","display_name":"Nianwen Ning","orcid":"https://orcid.org/0000-0001-9290-0361"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nianwen Ning","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100608154","display_name":"Bai Wang","orcid":"https://orcid.org/0009-0007-4592-795X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bai Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109339790"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59616801,"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":"757","last_page":"764"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"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/computer-science","display_name":"Computer science","score":0.8296482563018799},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6597820520401001},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5605573654174805},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5337273478507996},{"id":"https://openalex.org/keywords/interactivity","display_name":"Interactivity","score":0.43629390001296997},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3892322778701782},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3165796995162964},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13358920812606812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8296482563018799},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6597820520401001},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5605573654174805},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5337273478507996},{"id":"https://openalex.org/C144430266","wikidata":"https://www.wikidata.org/wiki/Q839721","display_name":"Interactivity","level":2,"score":0.43629390001296997},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3892322778701782},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3165796995162964},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13358920812606812}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3341161.3345643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341161.3345643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W37539912","https://openalex.org/W1888005072","https://openalex.org/W1981276685","https://openalex.org/W2000062922","https://openalex.org/W2054141820","https://openalex.org/W2074697575","https://openalex.org/W2077685126","https://openalex.org/W2083381833","https://openalex.org/W2124153111","https://openalex.org/W2137370514","https://openalex.org/W2145360759","https://openalex.org/W2149814409","https://openalex.org/W2151498529","https://openalex.org/W2154851992","https://openalex.org/W2167467982","https://openalex.org/W2168849769","https://openalex.org/W2185795907","https://openalex.org/W2242161203","https://openalex.org/W2331354824","https://openalex.org/W2336386265","https://openalex.org/W2337766690","https://openalex.org/W2475334473","https://openalex.org/W2533413719","https://openalex.org/W2585247128","https://openalex.org/W2739946816","https://openalex.org/W2782884631","https://openalex.org/W2811124557","https://openalex.org/W2884134047","https://openalex.org/W2896735086","https://openalex.org/W2947030669","https://openalex.org/W2962712142","https://openalex.org/W2962756421","https://openalex.org/W2962767366","https://openalex.org/W2963512530","https://openalex.org/W3104097132","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2001821990","https://openalex.org/W2319020389","https://openalex.org/W2272707781","https://openalex.org/W2747851897","https://openalex.org/W1975913006","https://openalex.org/W1513662110","https://openalex.org/W2063506784","https://openalex.org/W4240086805","https://openalex.org/W2521348551","https://openalex.org/W2013411520"],"abstract_inverted_index":{"Graph":[0,48],"has":[1],"been":[2],"widely":[3],"used":[4],"for":[5,77,94],"modeling":[6],"complex":[7],"relationship":[8],"datasets":[9],"in":[10,23,80],"different":[11,130],"application":[12],"fields.":[13],"Social":[14],"networks":[15],"based":[16,31,71,143],"recommendation":[17,29,69,79,106,142],"system":[18],"have":[19],"obtained":[20],"satisfactory":[21],"results":[22],"Business":[24],"Intelligence(BI).":[25],"However,":[26],"current":[27],"personalized":[28],"methods":[30],"on":[32,72,85,144,176],"graph":[33,160],"structure":[34],"generally":[35],"lack":[36],"interactivity":[37],"and":[38,104,161],"seldom":[39],"consider":[40],"efficient":[41,68],"data":[42,74],"management.":[43],"To":[44],"address":[45],"these":[46,147],"problems,":[47],"OnLine":[49],"Analytical":[50],"Mining":[51],"(GraphOLAM)":[52],"is":[53,96],"a":[54,88],"promising":[55],"method,":[56],"which":[57,98,120,149],"combines":[58,99],"OLAP":[59],"technology":[60,76],"with":[61],"social":[62],"networks.":[63],"We":[64],"first":[65],"propose":[66],"an":[67,177],"framework":[70,91],"GraphOLAM":[73,100,116],"cube":[75],"the":[78,81,122,127,139,152,155,158,165],"insurance":[82,95,178],"service.":[83],"Based":[84],"this":[86],"framework,":[87],"new":[89],"algorithm":[90],"named":[92],"RU-GOLAM":[93],"proposed,":[97],"dimensional":[101,117],"aggregation":[102,118],"operation":[103],"specific":[105],"methods.":[107],"A":[108],"series":[109],"of":[110,124,129,146,157,164],"graphs":[111],"can":[112,150],"be":[113],"generated":[114],"by":[115],"operations,":[119],"reflect":[121],"relationships":[123],"nodes":[125],"under":[126],"constraints":[128],"hierarchical":[131],"dimensions.":[132],"Node":[133],"similarities":[134],"are":[135],"calculated":[136],"to":[137],"generate":[138],"Top-N":[140],"sequential":[141],"all":[145],"graphs,":[148],"achieve":[151],"balance":[153],"between":[154],"topology":[156],"original":[159],"high-dimensional":[162],"information":[163],"nodes.":[166],"Experiments":[167],"show":[168],"that":[169],"our":[170],"approach":[171],"outperforms":[172],"other":[173],"baseline":[174],"algorithms":[175],"service":[179],"dataset.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}