{"id":"https://openalex.org/W2954822858","doi":"https://doi.org/10.1145/3331184.3331237","title":"Mention Recommendation in Twitter with Cooperative Multi-Agent Reinforcement Learning","display_name":"Mention Recommendation in Twitter with Cooperative Multi-Agent Reinforcement Learning","publication_year":2019,"publication_date":"2019-07-18","ids":{"openalex":"https://openalex.org/W2954822858","doi":"https://doi.org/10.1145/3331184.3331237","mag":"2954822858"},"language":"en","primary_location":{"id":"doi:10.1145/3331184.3331237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5058353652","display_name":"Tao Gui","orcid":"https://orcid.org/0000-0002-6154-0751"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Gui","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346918","display_name":"Peng Liu","orcid":"https://orcid.org/0009-0000-7271-4721"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Liu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360407","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0003-0947-4942"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013970731","display_name":"Liang Zhu","orcid":"https://orcid.org/0000-0002-0921-7076"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Zhu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070246702","display_name":"Minlong Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minlong Peng","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101481048","display_name":"Yunhua Zhou","orcid":"https://orcid.org/0000-0002-0180-5527"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhua Zhou","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xuanjing Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanjing Huang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"535","last_page":"544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9993000030517578,"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T11478","display_name":"Caching and Content Delivery","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8507161140441895},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6322493553161621},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6308999061584473},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5930413603782654},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4959040582180023},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4677218198776245},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.45059168338775635},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.44722995162010193},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4431125223636627},{"id":"https://openalex.org/keywords/symbol","display_name":"Symbol (formal)","score":0.427407443523407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3312714099884033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8507161140441895},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6322493553161621},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6308999061584473},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5930413603782654},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4959040582180023},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4677218198776245},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.45059168338775635},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.44722995162010193},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4431125223636627},{"id":"https://openalex.org/C134400042","wikidata":"https://www.wikidata.org/wiki/Q2372244","display_name":"Symbol (formal)","level":2,"score":0.427407443523407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3312714099884033},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3331184.3331237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3331184.3331237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","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":37,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1515851193","https://openalex.org/W1757796397","https://openalex.org/W1976320242","https://openalex.org/W1980358463","https://openalex.org/W1988354443","https://openalex.org/W1989341178","https://openalex.org/W2015209454","https://openalex.org/W2031237011","https://openalex.org/W2048508267","https://openalex.org/W2061761630","https://openalex.org/W2064675550","https://openalex.org/W2093219534","https://openalex.org/W2119717200","https://openalex.org/W2139575250","https://openalex.org/W2145339207","https://openalex.org/W2156737235","https://openalex.org/W2188869342","https://openalex.org/W2206595451","https://openalex.org/W2277660299","https://openalex.org/W2294143474","https://openalex.org/W2463565445","https://openalex.org/W2546696630","https://openalex.org/W2566089760","https://openalex.org/W2577986441","https://openalex.org/W2592798481","https://openalex.org/W2617547828","https://openalex.org/W2732016772","https://openalex.org/W2741859754","https://openalex.org/W2797234205","https://openalex.org/W2798775153","https://openalex.org/W2803085441","https://openalex.org/W2883944462","https://openalex.org/W2897470545","https://openalex.org/W2951268105","https://openalex.org/W2963658727","https://openalex.org/W2997591727"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4317039510","https://openalex.org/W4238861846","https://openalex.org/W790944756"],"abstract_inverted_index":{"In":[0,93],"Twitter-like":[1],"social":[2],"networking":[3],"services,":[4],"the":[5,12,18,24,30,83,90,98,139,148],"\"@''":[6],"symbol":[7],"can":[8,39,122],"be":[9],"used":[10,46],"with":[11],"tweet":[13],"to":[14,21,29,56,106],"mention":[15,107],"users":[16,75],"whom":[17],"user":[19,31,140],"wants":[20],"alert":[22],"regarding":[23],"message.":[25],"An":[26],"automatic":[27],"suggestion":[28],"of":[32,36,64,80,85,100,112,128],"a":[33,77,101,125],"small":[34,126],"list":[35,63],"candidate":[37],"names":[38],"improve":[40],"communication":[41],"efficiency.":[42],"Previous":[43],"work":[44],"usually":[45],"several":[47,86],"most":[48],"recent":[49],"tweets":[50,55,73,87,115,130,136],"or":[51],"randomly":[52],"select":[53,124],"historical":[54,72,114,129],"make":[57],"an":[58],"inference":[59],"about":[60],"this":[61,94],"preferred":[62],"names.":[65],"However,":[66],"because":[67],"there":[68],"are":[69],"too":[70],"many":[71],"by":[74],"and":[76,131,141],"wide":[78],"variety":[79],"content":[81],"types,":[82],"use":[84,99],"cannot":[88],"guarantee":[89],"desired":[91],"results.":[92],"work,":[95],"we":[96],"propose":[97],"novel":[102],"cooperative":[103],"multi-agent":[104],"approach":[105],"recommendation,":[108],"which":[109],"incorporates":[110],"dozens":[111],"more":[113],"than":[116],"earlier":[117],"approaches.":[118],"The":[119],"proposed":[120,149],"method":[121,150],"effectively":[123],"set":[127],"cooperatively":[132],"extract":[133],"relevant":[134],"indicator":[135],"from":[137],"both":[138],"mentioned":[142],"users.":[143],"Experimental":[144],"results":[145],"demonstrate":[146],"that":[147],"outperforms":[151],"state-of-the-art":[152],"methods.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
