{"id":"https://openalex.org/W2094612320","doi":"https://doi.org/10.1145/2396761.2398434","title":"Exploring and predicting search task difficulty","display_name":"Exploring and predicting search task difficulty","publication_year":2012,"publication_date":"2012-10-29","ids":{"openalex":"https://openalex.org/W2094612320","doi":"https://doi.org/10.1145/2396761.2398434","mag":"2094612320"},"language":"en","primary_location":{"id":"doi:10.1145/2396761.2398434","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","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/A5100442553","display_name":"Jingjing Liu","orcid":"https://orcid.org/0000-0001-8510-2003"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingjing Liu","raw_affiliation_strings":["University of South Carolina, Columbia, SC, USA","University of South Carolina, columbia, SC, USA,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]},{"raw_affiliation_string":"University of South Carolina, columbia, SC, USA,","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353313","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0002-9183-6385"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029883057","display_name":"Michael Cole","orcid":"https://orcid.org/0000-0001-9729-3898"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Cole","raw_affiliation_strings":["Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000241132","display_name":"Nicholas J. Belkin","orcid":"https://orcid.org/0000-0002-0621-0688"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas J. Belkin","raw_affiliation_strings":["Rutgers University, New Brunwick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, New Brunwick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101503268","display_name":"Xiangmin Zhang","orcid":"https://orcid.org/0000-0001-9285-1619"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangmin Zhang","raw_affiliation_strings":["Wayne State University, Detroit, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1112,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.94735304,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1313","last_page":"1322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9977999925613403,"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":0.9977999925613403,"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":0.9860000014305115,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9603999853134155,"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/session","display_name":"Session (web analytics)","score":0.7983400821685791},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7911023497581482},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7689770460128784},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.529365062713623},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49262839555740356},{"id":"https://openalex.org/keywords/time-point","display_name":"Time point","score":0.440005362033844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43721118569374084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07734298706054688},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07027170062065125}],"concepts":[{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.7983400821685791},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7911023497581482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689770460128784},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.529365062713623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49262839555740356},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.440005362033844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43721118569374084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07734298706054688},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07027170062065125},{"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2396761.2398434","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.01RUT_INST:11664898660004646","is_oa":false,"landing_page_url":"https://scholarship.libraries.rutgers.edu/esploro/outputs/conferenceProceeding/Exploring-and-predicting-search-task-difficulty/991031665315604646","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"Open Research (University of Surrey)","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306122","display_name":"Institute of Museum and Library Services","ror":"https://ror.org/030prv062"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1602958214","https://openalex.org/W1971206868","https://openalex.org/W1981261334","https://openalex.org/W2004591793","https://openalex.org/W2006202170","https://openalex.org/W2007750197","https://openalex.org/W2008251177","https://openalex.org/W2057024235","https://openalex.org/W2069091827","https://openalex.org/W2079168273","https://openalex.org/W2104255729","https://openalex.org/W2114453188","https://openalex.org/W2123937625","https://openalex.org/W2124318441","https://openalex.org/W2130900715","https://openalex.org/W2137366811","https://openalex.org/W2145781566","https://openalex.org/W2160111441","https://openalex.org/W2161598049","https://openalex.org/W2164734124"],"related_works":["https://openalex.org/W3087157779","https://openalex.org/W4306770904","https://openalex.org/W2348742136","https://openalex.org/W4231927834","https://openalex.org/W2961085424","https://openalex.org/W1965155517","https://openalex.org/W4306674287","https://openalex.org/W4382052975","https://openalex.org/W4224009465","https://openalex.org/W1971206868"],"abstract_inverted_index":{"We":[0,51,172],"report":[1],"on":[2],"an":[3],"investigation":[4],"of":[5,84,100,108,141,184,193,198],"behavioral":[6],"differences":[7],"between":[8,116],"users":[9],"in":[10,22,34,47],"difficult":[11,119],"and":[12,93,118,131,138,209],"easy":[13,117],"search":[14,45,204,211],"tasks.":[15,120],"Behavioral":[16],"factors":[17],"that":[18,56,105,175],"can":[19,57,73,188,202],"be":[20,58,74],"used":[21],"real-time":[23,134,167],"to":[24,213],"predict":[25,206],"task":[26,123,207],"difficulty":[27,124,208],"are":[28,165],"identified.":[29],"User":[30],"data":[31],"was":[32],"collected":[33],"a":[35,106,181,190,196],"controlled":[36],"lab":[37],"experiment":[38],"(n=38)":[39],"where":[40],"each":[41],"participant":[42],"completed":[43],"four":[44],"tasks":[46],"the":[48,67,71,82,85,91,98,101,157,160],"genomics":[49],"domain.":[50],"looked":[52],"at":[53,62,81,111,125],"user":[54,109],"behaviors":[55,110,142,163],"obtained":[59],"by":[60,66,97],"systems":[61,205],"three":[63,113,127],"levels,":[64],"distinguished":[65],"time":[68],"point":[69],"when":[70],"measurements":[72],"done.":[75],"They":[76],"are:":[77],"1)":[78],"first-round":[79,137],"level":[80,89,96,162],"beginning":[83],"search,":[86,92],"2)":[87],"accumulated":[88,139],"during":[90],"3)":[94],"whole-session":[95,161],"end":[99],"search.":[102],"Results":[103],"show":[104],"number":[107,183],"all":[112,126],"levels":[114,128,140],"differed":[115],"Models":[121],"predicting":[122],"were":[129],"developed":[130],"evaluated.":[132],"A":[133],"model":[135,158],"incorporating":[136],"(FA)":[143],"had":[144],"fairly":[145],"good":[146],"prediction":[147,191],"performance":[148],"(accuracy":[149,168],"83%;":[150],"precision":[151,170,197],"88%),":[152],"which":[153,164],"is":[154],"comparable":[155],"with":[156,195],"using":[159,179],"not":[166],"75%;":[169],"92%).":[171],"also":[173],"found":[174],"for":[176],"efficiency":[177],"purpose,":[178],"only":[180],"limited":[182],"significant":[185],"variables":[186],"(FC_FA)":[187],"obtain":[189],"accuracy":[192],"75%,":[194],"88%.":[199],"Our":[200],"findings":[201],"help":[203],"adapt":[210],"results":[212],"users.":[214]},"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":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":4}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
