{"id":"https://openalex.org/W2964041372","doi":"https://doi.org/10.24963/ijcai.2018/459","title":"Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback","display_name":"Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2964041372","doi":"https://doi.org/10.24963/ijcai.2018/459","mag":"2964041372"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/459","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/459","pdf_url":"https://www.ijcai.org/proceedings/2018/0459.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0459.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100444482","display_name":"Kun Chen","orcid":"https://orcid.org/0000-0003-2370-5372"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Chen","raw_affiliation_strings":["Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088801513","display_name":"Kechao Cai","orcid":"https://orcid.org/0000-0003-4354-0843"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kechao Cai","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082905458","display_name":"Longbo Huang","orcid":"https://orcid.org/0000-0002-7341-447X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longbo Huang","raw_affiliation_strings":["Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068489266","display_name":"John C. S. Lui","orcid":"https://orcid.org/0000-0001-7466-0384"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"John C.S. Lui","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.321,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8387955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3308","last_page":"3314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12288","display_name":"Optimization and Search Problems","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9882000088691711,"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":0.6972801089286804},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6918795108795166},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6107346415519714},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5594409704208374},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.5547255873680115},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.5374622344970703},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5105479955673218},{"id":"https://openalex.org/keywords/attractiveness","display_name":"Attractiveness","score":0.49446702003479004},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.4943413734436035},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.45487746596336365},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2632024884223938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22901347279548645},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2216382920742035},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1898268461227417},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08320885896682739},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.0801800787448883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972801089286804},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6918795108795166},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6107346415519714},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5594409704208374},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.5547255873680115},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.5374622344970703},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5105479955673218},{"id":"https://openalex.org/C31173074","wikidata":"https://www.wikidata.org/wiki/Q2632514","display_name":"Attractiveness","level":2,"score":0.49446702003479004},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.4943413734436035},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.45487746596336365},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2632024884223938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22901347279548645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2216382920742035},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1898268461227417},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08320885896682739},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0801800787448883},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/459","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/459","pdf_url":"https://www.ijcai.org/proceedings/2018/0459.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/459","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/459","pdf_url":"https://www.ijcai.org/proceedings/2018/0459.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G571721012","display_name":null,"funder_award_id":"61303195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G72957147","display_name":null,"funder_award_id":"61672316","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964041372.pdf","grobid_xml":"https://content.openalex.org/works/W2964041372.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1562129026","https://openalex.org/W1569127318","https://openalex.org/W1702271787","https://openalex.org/W1850547517","https://openalex.org/W1999678910","https://openalex.org/W2007604989","https://openalex.org/W2026807222","https://openalex.org/W2029241234","https://openalex.org/W2070815407","https://openalex.org/W2112420033","https://openalex.org/W2115519224","https://openalex.org/W2125724988","https://openalex.org/W2185823609","https://openalex.org/W2400128071","https://openalex.org/W2404446105","https://openalex.org/W2410288126","https://openalex.org/W2418554883","https://openalex.org/W2441269247","https://openalex.org/W2559882344","https://openalex.org/W2573607665","https://openalex.org/W2950929549","https://openalex.org/W2962727139","https://openalex.org/W2962818688","https://openalex.org/W2964041372","https://openalex.org/W2964295918","https://openalex.org/W4245039430","https://openalex.org/W4252816727"],"related_works":["https://openalex.org/W2614563012","https://openalex.org/W2971351794","https://openalex.org/W4376155396","https://openalex.org/W4293337373","https://openalex.org/W1947085858","https://openalex.org/W1968533609","https://openalex.org/W2174986909","https://openalex.org/W2527791220","https://openalex.org/W1984270607","https://openalex.org/W2101991911"],"abstract_inverted_index":{"The":[0,120],"web":[1,12,17,28,82,97],"link":[2,18,57,98,138,156],"selection":[3,99,157],"problem":[4,125,144],"is":[5,104,113,126,139],"to":[6,21,74,105],"select":[7],"a":[8,15,27,34,117,146],"small":[9],"subset":[10],"of":[11,37,55,123,176],"links":[13,25,83],"from":[14,64],"large":[16],"pool,":[19],"and":[20,134,152,174,189],"place":[22],"the":[23,46,53,56,75,95,102,111,124,137,177,199],"selected":[24],"on":[26,171,185],"page":[29],"that":[30,110,127,191],"can":[31,60],"only":[32,61],"accommodate":[33],"limited":[35],"number":[36],"links,":[38],"e.g.,":[39,69],"advertisements,":[40],"recommendations,":[41],"or":[42],"news":[43],"feeds.":[44],"Despite":[45],"long":[47],"concerned":[48],"click-through":[49],"rate":[50],"which":[51],"reflects":[52],"attractiveness":[54,112,178],"itself,":[58],"revenue":[59,107],"be":[62],"obtained":[63],"user":[65],"actions":[66],"after":[67,71],"clicks,":[68],"purchasing":[70],"being":[72],"directed":[73],"product":[76],"pages":[77],"by":[78],"recommendation":[79],"links.":[80],"Thus,":[81],"have":[84],"an":[85,154],"intrinsic":[86],"multi-level":[87,130,200],"feedback":[88,201],"structure.":[89,202],"With":[90],"this":[91,143],"observation,":[92],"we":[93],"consider":[94],"context-free":[96,195],"problem,":[100],"where":[101],"objective":[103],"maximize":[106],"while":[108],"ensuring":[109],"no":[114],"less":[115],"than":[116],"preset":[118],"threshold.":[119],"key":[121],"challenge":[122],"each":[128],"link's":[129],"feedbacks":[131],"are":[132],"stochastic,":[133],"unobservable":[135],"unless":[136],"selected.":[140],"We":[141,166,180],"model":[142],"with":[145],"constrained":[147],"stochastic":[148],"multi-armed":[149],"bandit":[150,196],"formulation,":[151],"design":[153],"efficient":[155],"algorithm,":[158],"called":[159],"Constrained":[160],"Upper":[161],"Confidence":[162],"Bound":[163],"algorithm":[164],"(Con-UCB).":[165],"prove":[167],"O(sqrt(T":[168],"ln(T)))":[169],"bounds":[170],"both":[172],"regret":[173],"violation":[175],"constraint.":[179],"also":[181],"conduct":[182],"extensive":[183],"experiments":[184],"three":[186],"real-world":[187],"datasets,":[188],"show":[190],"Con-UCB":[192],"outperforms":[193],"state-of-the-art":[194],"algorithms":[197],"concerning":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}