{"id":"https://openalex.org/W1970977883","doi":"https://doi.org/10.1145/2391224.2391227","title":"Modeling user variance in time-biased gain","display_name":"Modeling user variance in time-biased gain","publication_year":2012,"publication_date":"2012-10-04","ids":{"openalex":"https://openalex.org/W1970977883","doi":"https://doi.org/10.1145/2391224.2391227","mag":"1970977883"},"language":"en","primary_location":{"id":"doi:10.1145/2391224.2391227","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2391224.2391227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Symposium on Human-Computer Interaction and 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/A5049222552","display_name":"Mark D. Smucker","orcid":"https://orcid.org/0000-0003-4968-6405"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mark D. Smucker","raw_affiliation_strings":["University of Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037737168","display_name":"Charles L. A. Clarke","orcid":"https://orcid.org/0000-0001-8178-9194"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Charles L. A. Clarke","raw_affiliation_strings":["University of Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9998000264167786,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9998000264167786,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9937999844551086,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/variance","display_name":"Variance (accounting)","score":0.8074741363525391},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7547866702079773},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.694133996963501},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.583358645439148},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.43872907757759094},{"id":"https://openalex.org/keywords/information-gain","display_name":"Information gain","score":0.4232301115989685},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3980581760406494},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3250148892402649},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08587732911109924}],"concepts":[{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.8074741363525391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7547866702079773},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.694133996963501},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.583358645439148},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.43872907757759094},{"id":"https://openalex.org/C2983203078","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Information gain","level":2,"score":0.4232301115989685},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3980581760406494},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3250148892402649},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08587732911109924},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2391224.2391227","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2391224.2391227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.298.2742","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.2742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://plg.uwaterloo.ca/~claclark/smucker-clarke-hcir2012-user-variance.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W132343450","https://openalex.org/W612372977","https://openalex.org/W1590622490","https://openalex.org/W1968927634","https://openalex.org/W1992411228","https://openalex.org/W2017633929","https://openalex.org/W2026430213","https://openalex.org/W2029009258","https://openalex.org/W2031858317","https://openalex.org/W2037377096","https://openalex.org/W2039605493","https://openalex.org/W2046011778","https://openalex.org/W2047860186","https://openalex.org/W2054725756","https://openalex.org/W2069870183","https://openalex.org/W2071156242","https://openalex.org/W2099048704","https://openalex.org/W2100548715","https://openalex.org/W2106532293","https://openalex.org/W2111310810","https://openalex.org/W2120966432","https://openalex.org/W2129874624","https://openalex.org/W2134440707","https://openalex.org/W2135805712","https://openalex.org/W2148545726","https://openalex.org/W2152707065","https://openalex.org/W2156186232","https://openalex.org/W2170121748","https://openalex.org/W2621408339"],"related_works":["https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W1891216533","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2276587472","https://openalex.org/W2615795876","https://openalex.org/W2049612369","https://openalex.org/W2770872919","https://openalex.org/W4399207312"],"abstract_inverted_index":{"Cranfield-style":[0],"information":[1,8],"retrieval":[2,12,62],"evaluation":[3,103],"considers":[4],"variance":[5,41,54,68,85,164],"in":[6,32,42,165],"user":[7,53,67,81,94,107],"needs":[9],"by":[10,143,158],"evaluating":[11],"systems":[13],"over":[14],"a":[15,87,162],"set":[16],"of":[17,46,59,66,75,86,126,140,149,175,179],"search":[18,22],"topics.":[19],"For":[20],"each":[21],"topic,":[23],"traditional":[24],"metrics":[25],"model":[26,52,130],"all":[27],"users":[28],"searching":[29],"ranked":[30,110],"lists":[31,111],"exactly":[33],"the":[34,56,73,79,84,91,123,131,173,176,186],"same":[35],"manner":[36],"and":[37],"thus":[38],"have":[39],"zero":[40],"their":[43],"per-topic":[44,163],"estimate":[45],"effectiveness.":[47],"Metrics":[48],"that":[49,105,112,145,151],"fail":[50],"to":[51,71,129,184,188,194],"overestimate":[55],"effect":[57,92,177],"size":[58,178],"differences":[60,77],"between":[61,133],"systems.":[63],"The":[64],"modeling":[65],"is":[69,89,101],"critical":[70],"understanding":[72],"impact":[74],"effectiveness":[76,167],"on":[78,93],"actual":[80,155],"experience.":[82],"If":[83],"difference":[88],"high,":[90],"experience":[95],"will":[96],"be":[97],"low.":[98],"Time-biased":[99],"gain":[100,128,142,150,170],"an":[102],"metric":[104],"models":[106],"interaction":[108],"with":[109,154],"are":[113],"displayed":[114],"using":[115],"document":[116],"surrogates.":[117],"In":[118],"this":[119,137],"paper,":[120],"we":[121],"extend":[122],"stochastic":[124],"simulation":[125],"time-biased":[127,141,169],"variation":[132],"users.":[134,160,196],"We":[135],"validate":[136],"new":[138],"version":[139],"showing":[144],"it":[146],"produces":[147],"distributions":[148,156],"agree":[152],"well":[153],"produced":[157],"real":[159,195],"With":[161],"its":[166],"measure,":[168],"allows":[171,182],"for":[172],"measurement":[174],"differences,":[180],"which":[181,189],"researchers":[183],"understand":[185],"extent":[187],"predicted":[190],"performance":[191],"improvements":[192],"matter":[193]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}