{"id":"https://openalex.org/W2550455676","doi":"https://doi.org/10.1109/ijcnn.2016.7727520","title":"Predicting user's multi-interests with network embedding in health-related topics","display_name":"Predicting user's multi-interests with network embedding in health-related topics","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2550455676","doi":"https://doi.org/10.1109/ijcnn.2016.7727520","mag":"2550455676"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5101725735","display_name":"Zhipeng Jin","orcid":"https://orcid.org/0009-0003-0863-2539"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Jin","raw_affiliation_strings":["Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066267829","display_name":"Ruoran Liu","orcid":"https://orcid.org/0000-0003-1510-4198"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruoran Liu","raw_affiliation_strings":["The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024206808","display_name":"Qiudan Li","orcid":"https://orcid.org/0000-0002-8714-4562"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiudan Li","raw_affiliation_strings":["Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038521974","display_name":"Daniel Zeng","orcid":"https://orcid.org/0000-0002-9046-222X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Daniel D. Zeng","raw_affiliation_strings":["Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA","The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014795463","display_name":"Yongcheng Zhan","orcid":"https://orcid.org/0000-0002-5029-0961"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"YongCheng Zhan","raw_affiliation_strings":["Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA"],"affiliations":[{"raw_affiliation_string":"Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435848","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-0961-0441"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101725735"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":2.9993,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.9299285,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2568","last_page":"2575"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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":0.9941999912261963,"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":0.9904000163078308,"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/computer-science","display_name":"Computer science","score":0.7627084255218506},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7411260008811951},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.606570839881897},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5205144286155701},{"id":"https://openalex.org/keywords/user-information","display_name":"User information","score":0.48037606477737427},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.450729101896286},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.4478050470352173},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4000462293624878},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3626418113708496},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.35309743881225586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2965078353881836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2619556784629822},{"id":"https://openalex.org/keywords/information-system","display_name":"Information system","score":0.17175588011741638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7627084255218506},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7411260008811951},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.606570839881897},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5205144286155701},{"id":"https://openalex.org/C2777622855","wikidata":"https://www.wikidata.org/wiki/Q7901844","display_name":"User information","level":3,"score":0.48037606477737427},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.450729101896286},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.4478050470352173},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4000462293624878},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3626418113708496},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.35309743881225586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2965078353881836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2619556784629822},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.17175588011741638},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical 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/ijcnn.2016.7727520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W852557563","https://openalex.org/W1495353771","https://openalex.org/W1614298861","https://openalex.org/W1964869462","https://openalex.org/W2004091058","https://openalex.org/W2007650067","https://openalex.org/W2010639892","https://openalex.org/W2016397589","https://openalex.org/W2021363300","https://openalex.org/W2041252375","https://openalex.org/W2053081145","https://openalex.org/W2059750639","https://openalex.org/W2075210203","https://openalex.org/W2080223600","https://openalex.org/W2080817720","https://openalex.org/W2085826953","https://openalex.org/W2098655743","https://openalex.org/W2114389382","https://openalex.org/W2117130368","https://openalex.org/W2147768505","https://openalex.org/W2151014496","https://openalex.org/W2154851992","https://openalex.org/W2161138645","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2168378693","https://openalex.org/W2168627253","https://openalex.org/W2177637414","https://openalex.org/W2251541206","https://openalex.org/W2978452692","https://openalex.org/W3104097132","https://openalex.org/W4211139322","https://openalex.org/W6636510571","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2067317451","https://openalex.org/W2154771632","https://openalex.org/W4211085505","https://openalex.org/W2084758217","https://openalex.org/W3122478268","https://openalex.org/W2183306018","https://openalex.org/W408804804","https://openalex.org/W2549990292","https://openalex.org/W2077885602"],"abstract_inverted_index":{"With":[0],"the":[1,65,93,191,194],"rapid":[2],"growth":[3],"of":[4,111,151,160,174,193],"Web":[5],"2.0,":[6],"social":[7],"media":[8],"has":[9],"become":[10],"a":[11,114,141,158],"prevalent":[12],"information":[13,56,95,118,150],"sharing":[14],"and":[15,29,33,68,165],"seeking":[16],"channel":[17],"for":[18,58,129],"health":[19],"surveillance,":[20],"in":[21,45,75,113],"which":[22,124,177],"users":[23,131],"form":[24],"interactive":[25,47],"networks":[26,48],"by":[27,101],"posting":[28],"replying":[30],"messages,":[31],"providing":[32],"rating":[34],"reviews,":[35],"attending":[36],"multiple":[37,51],"discussion":[38],"boards":[39],"on":[40,80,86,147,184],"health-related":[41,188],"topics.":[42],"Users'":[43],"behaviors":[44],"these":[46],"reflect":[49],"users'":[50,70,77,180],"interests.":[52,181],"To":[53],"provide":[54],"better":[55],"service":[57],"users,":[59],"it":[60],"is":[61,154,167],"necessary":[62],"to":[63,91,96,169],"analyze":[64],"user":[66,134,152,175],"interactions":[67,153],"predict":[69],"multi-interests.":[71],"Most":[72],"existing":[73],"work":[74],"predicting":[76,130],"multi-interests":[78,132,143],"based":[79,146],"multi":[81],"label":[82,107],"network":[83,115],"classification":[84,98],"focuses":[85],"using":[87,116],"approximate":[88],"inference":[89],"methods":[90],"leverage":[92],"dependency":[94],"improve":[97],"results.":[99],"Inspired":[100],"deep":[102],"learning":[103],"techniques,":[104],"DEEPWALK":[105],"learns":[106],"independent":[108],"latent":[109],"representations":[110,173],"vertices":[112],"local":[117],"obtained":[119],"from":[120,133],"truncated":[121],"random":[122,163],"walks,":[123],"provides":[125],"an":[126],"efficient":[127],"way":[128],"interactions.":[135],"In":[136],"this":[137],"paper,":[138],"we":[139],"develop":[140],"user's":[142],"prediction":[144],"model":[145],"DEEPWALK,":[148],"weight":[149],"considered":[155],"when":[156],"modeling":[157],"stream":[159],"short":[161],"constrained":[162],"walks":[164],"SkipGram":[166],"employed":[168],"generate":[170],"more":[171],"accurate":[172],"vertices,":[176],"help":[178],"identify":[179],"Experimental":[182],"results":[183],"two":[185],"real":[186],"world":[187],"datasets":[189],"show":[190],"efficacy":[192],"proposed":[195],"model.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
