{"id":"https://openalex.org/W1982204215","doi":"https://doi.org/10.1145/2766462.2767721","title":"Different Users, Different Opinions","display_name":"Different Users, Different Opinions","publication_year":2015,"publication_date":"2015-08-04","ids":{"openalex":"https://openalex.org/W1982204215","doi":"https://doi.org/10.1145/2766462.2767721","mag":"1982204215"},"language":"en","primary_location":{"id":"doi:10.1145/2766462.2767721","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2766462.2767721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th 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/A5100668121","display_name":"Yiqun Liu","orcid":"https://orcid.org/0000-0002-0140-4512"},"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":true,"raw_author_name":"Yiqun Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359095","display_name":"Ye Chen","orcid":"https://orcid.org/0000-0002-1080-7671"},"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":"Ye Chen","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China","Nanjing University of Science and Technology,,,Nanjing,,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Nanjing University of Science and Technology,,,Nanjing,,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024455283","display_name":"Jiashen Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiashen Sun","raw_affiliation_strings":["Samsung R&amp;D Institute China - Beijing, Beijing, China","Samsung R&D Institute China - Beijing, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute China - Beijing, Beijing, China","institution_ids":["https://openalex.org/I4210155230"]},{"raw_affiliation_string":"Samsung R&D Institute China - Beijing, Beijing, China#TAB#","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402996","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0003-3158-1920"},"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":"Min Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760812","display_name":"Shaoping Ma","orcid":"https://orcid.org/0000-0002-8762-8268"},"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":"Shaoping Ma","raw_affiliation_strings":["Tsinghua Unversity, Beijing, China","Tsinghua Unversity, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Tsinghua Unversity, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Unversity, Beijing, China#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101867825","display_name":"Xuan Zhu","orcid":"https://orcid.org/0000-0002-8422-2828"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Zhu","raw_affiliation_strings":["Samsung R&amp;D Institute China - Beijing, Beijing, China","Samsung R&D Institute China - Beijing, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Samsung R&amp;D Institute China - Beijing, Beijing, China","institution_ids":["https://openalex.org/I4210155230"]},{"raw_affiliation_string":"Samsung R&D Institute China - Beijing, Beijing, China#TAB#","institution_ids":["https://openalex.org/I4210155230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100668121"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":12.8999,"has_fulltext":false,"cited_by_count":72,"citation_normalized_percentile":{"value":0.98624554,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"493","last_page":"502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9973000288009644,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9973000288009644,"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/T11106","display_name":"Data Management and Algorithms","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9932000041007996,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7737977504730225},{"id":"https://openalex.org/keywords/judgement","display_name":"Judgement","score":0.6280414462089539},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5551224946975708},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5076848268508911},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.4811340868473053},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46901243925094604},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4687051475048065},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.467422217130661},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4401886463165283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29490160942077637},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09526672959327698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7737977504730225},{"id":"https://openalex.org/C2776548248","wikidata":"https://www.wikidata.org/wiki/Q12621536","display_name":"Judgement","level":2,"score":0.6280414462089539},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5551224946975708},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5076848268508911},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.4811340868473053},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46901243925094604},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4687051475048065},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.467422217130661},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4401886463165283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29490160942077637},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09526672959327698},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"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:10.1145/2766462.2767721","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2766462.2767721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th 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":29,"referenced_works":["https://openalex.org/W1590698834","https://openalex.org/W1597379241","https://openalex.org/W1976187638","https://openalex.org/W2003658560","https://openalex.org/W2007750197","https://openalex.org/W2008251177","https://openalex.org/W2012430612","https://openalex.org/W2035569891","https://openalex.org/W2036823777","https://openalex.org/W2037789405","https://openalex.org/W2038385982","https://openalex.org/W2058473041","https://openalex.org/W2060890758","https://openalex.org/W2073171099","https://openalex.org/W2096438175","https://openalex.org/W2099302229","https://openalex.org/W2106817091","https://openalex.org/W2119074598","https://openalex.org/W2120889650","https://openalex.org/W2122536076","https://openalex.org/W2128160875","https://openalex.org/W2134099522","https://openalex.org/W2141281266","https://openalex.org/W2150137742","https://openalex.org/W2153082595","https://openalex.org/W2154105380","https://openalex.org/W2158254843","https://openalex.org/W2165474780","https://openalex.org/W2403321187"],"related_works":["https://openalex.org/W2886802431","https://openalex.org/W4388216822","https://openalex.org/W1761762290","https://openalex.org/W4391191813","https://openalex.org/W4387575966","https://openalex.org/W2384262901","https://openalex.org/W2975214487","https://openalex.org/W651304006","https://openalex.org/W2345720417","https://openalex.org/W2529033802"],"abstract_inverted_index":{"Satisfaction":[0],"prediction":[1,45],"is":[2,13,26],"one":[3],"of":[4,24,63,119,153],"the":[5,97,117,126,151,157,175,208],"prime":[6],"concerns":[7],"in":[8,36,129,136,159],"search":[9,76,100,111,130,154,160,170],"performance":[10],"evaluation.":[11],"It":[12],"a":[14],"non-trivial":[15],"task":[16],"for":[17,96,196,220],"two":[18,181],"major":[19],"reasons:":[20],"(1)":[21],"The":[22],"definition":[23],"satisfaction":[25,37,44,82,197],"rather":[27],"subjective":[28],"and":[29,102,156,186,214,223],"different":[30,34,221],"users":[31,112,222],"may":[32],"have":[33,216],"opinions":[35,105],"judgement.":[38],"(2)":[39],"Most":[40],"existing":[41,92,176,212],"studies":[42,135],"on":[43,48,68,106,125,141,169,201],"mainly":[46],"rely":[47],"users'":[49,81,101],"click-through":[50],"or":[51],"query":[52],"reformulation":[53],"behaviors":[54],"but":[55],"there":[56],"are":[57,188],"many":[58],"sessions":[59,161,205],"without":[60],"such":[61],"kind":[62],"interactions.":[64],"To":[65],"shed":[66],"light":[67],"these":[69],"research":[70],"questions,":[71],"we":[72,94,147],"construct":[73],"an":[74],"experimental":[75],"engine":[77],"that":[78,110,207],"could":[79],"collect":[80],"feedback":[83],"as":[84,86],"well":[85],"mouse":[87,142,166],"click-through/movement":[88],"data.":[89],"Different":[90],"from":[91,165],"studies,":[93],"compare":[95],"first":[98],"time":[99],"external":[103,122],"assessors'":[104],"satisfaction.":[107],"We":[108],"find":[109],"pay":[113],"more":[114],"attention":[115],"to":[116,149,191],"utility":[118],"results":[120,155,200],"while":[121],"assessors":[123],"emphasize":[124],"efforts":[127,158],"spent":[128],"sessions.":[131],"Inspired":[132],"by":[133],"recent":[134],"predicting":[137],"result":[138,171],"relevance":[139],"based":[140],"movement":[143,167],"patterns":[144],"(namely":[145],"motifs),":[146],"propose":[148],"estimate":[150],"utilities":[152],"with":[162],"motifs":[163,195],"extracted":[164],"data":[168],"pages":[172],"(SERPs).":[173],"Besides":[174],"frequency-based":[177],"motif":[178],"selection":[179,183],"method,":[180],"novel":[182],"strategies":[184,210],"(distance-based":[185],"distribution-based)":[187],"also":[189,215],"adopted":[190],"extract":[192],"high":[193],"quality":[194],"prediction.":[198],"Experimental":[199],"over":[202],"1,000":[203],"user":[204],"show":[206],"proposed":[209],"outperform":[211],"methods":[213],"promising":[217],"generalization":[218],"capability":[219],"queries.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
