{"id":"https://openalex.org/W2741516097","doi":"https://doi.org/10.1145/3077136.3080670","title":"A Poisson Regression Method for Top-N Recommendation","display_name":"A Poisson Regression Method for Top-N Recommendation","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2741516097","doi":"https://doi.org/10.1145/3077136.3080670","mag":"2741516097"},"language":"en","primary_location":{"id":"doi:10.1145/3077136.3080670","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5079270412","display_name":"Jiajin Huang","orcid":"https://orcid.org/0000-0002-7495-3440"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiajin Huang","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100696824","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-4316-932X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022096691","display_name":"Ning Zhong","orcid":"https://orcid.org/0000-0001-7882-8340"},"institutions":[{"id":"https://openalex.org/I153470267","display_name":"Maebashi Institute of Technology","ror":"https://ror.org/01x05rm94","country_code":"JP","type":"education","lineage":["https://openalex.org/I153470267"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ning Zhong","raw_affiliation_strings":["Maebashi Institute of Technology, Maebashi, Japan"],"affiliations":[{"raw_affiliation_string":"Maebashi Institute of Technology, Maebashi, Japan","institution_ids":["https://openalex.org/I153470267"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079270412"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08009885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"885","last_page":"888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9983999729156494,"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/T11478","display_name":"Caching and Content Delivery","score":0.973800003528595,"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/poisson-regression","display_name":"Poisson regression","score":0.793778657913208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7473986744880676},{"id":"https://openalex.org/keywords/information-overload","display_name":"Information overload","score":0.7065812349319458},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6827297210693359},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6391903162002563},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5861497521400452},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.49993371963500977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46513646841049194},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.46494925022125244},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4548393785953522},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.4395866394042969},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.42453476786613464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3973221182823181},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33453384041786194},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27832651138305664},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.2555080056190491},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18315920233726501}],"concepts":[{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.793778657913208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473986744880676},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.7065812349319458},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6827297210693359},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6391903162002563},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5861497521400452},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.49993371963500977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46513646841049194},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.46494925022125244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4548393785953522},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.4395866394042969},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.42453476786613464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3973221182823181},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33453384041786194},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27832651138305664},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2555080056190491},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18315920233726501},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3077136.3080670","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1672791804","https://openalex.org/W1984127251","https://openalex.org/W2047109571","https://openalex.org/W2060754265","https://openalex.org/W2067668838","https://openalex.org/W2070915285","https://openalex.org/W2097533650","https://openalex.org/W2110953678","https://openalex.org/W2137245235","https://openalex.org/W2164278908","https://openalex.org/W2511264801","https://openalex.org/W2962818688","https://openalex.org/W3101685505","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W4251329182","https://openalex.org/W1599110641","https://openalex.org/W1549403601","https://openalex.org/W2497510784","https://openalex.org/W4252183363","https://openalex.org/W2787177576","https://openalex.org/W2078352417","https://openalex.org/W2418053903","https://openalex.org/W2098758514","https://openalex.org/W1575740715"],"abstract_inverted_index":{"Top-N":[0],"recommendation":[1,45],"tasks":[2],"aim":[3],"to":[4,38],"solve":[5],"the":[6,13,32,60,64,67,72,88],"information":[7,14],"overload":[8],"problem":[9],"for":[10,43],"users":[11],"in":[12],"age.":[15],"As":[16],"a":[17,40,53],"user's":[18],"decision":[19],"may":[20],"be":[21],"affected":[22],"by":[23],"correlations":[24,30],"among":[25],"items,":[26],"we":[27],"incorporate":[28],"such":[29],"with":[31],"user":[33],"and":[34,51,63],"item":[35],"latent":[36,61],"factors":[37,62],"propose":[39],"Poisson-regression-based":[41],"method":[42,58,75],"top-N":[44],"tasks.":[46],"By":[47],"placing":[48],"priori":[49],"knowledge":[50],"using":[52],"sparse":[54],"structure":[55,65],"assumption,":[56],"this":[57],"learns":[59],"of":[66,76,91],"item-item":[68],"correlation":[69],"matrix":[70],"through":[71],"alternating":[73],"direction":[74],"multipliers":[77],"(ADMM).":[78],"The":[79],"preliminary":[80],"experimental":[81],"results":[82],"on":[83],"two":[84],"real-world":[85],"datasets":[86],"show":[87],"improved":[89],"performance":[90],"our":[92],"approach.":[93]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}