{"id":"https://openalex.org/W3094126542","doi":"https://doi.org/10.1145/3340531.3417454","title":"Empirical Analysis of Impact of Query-Specific Customization of nDCG","display_name":"Empirical Analysis of Impact of Query-Specific Customization of nDCG","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3094126542","doi":"https://doi.org/10.1145/3340531.3417454","mag":"3094126542"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3417454","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3417454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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/A5053287819","display_name":"Shubhra Kanti Karmaker","orcid":"https://orcid.org/0000-0001-5744-6925"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shubhra (Santu) K. Karmaker","raw_affiliation_strings":["Auburn University, Auburn, AL, USA"],"affiliations":[{"raw_affiliation_string":"Auburn University, Auburn, AL, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001811638","display_name":"Parikshit Sondhi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Parikshit Sondhi","raw_affiliation_strings":["Snap Inc., Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Snap Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028518494","display_name":"ChengXiang Zhai","orcid":"https://orcid.org/0000-0002-6434-3702"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"ChengXiang Zhai","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053287819"],"corresponding_institution_ids":["https://openalex.org/I82497590"],"apc_list":null,"apc_paid":null,"fwci":1.6649,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88565323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3281","last_page":"3284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9990000128746033,"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":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9955999851226807,"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":0.7704072594642639},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.7524659633636475},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.722643256187439},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.45793959498405457},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4436336159706116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3611202836036682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33352482318878174},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1030900776386261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7704072594642639},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.7524659633636475},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.722643256187439},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45793959498405457},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4436336159706116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3611202836036682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33352482318878174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1030900776386261},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3417454","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3417454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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":14,"referenced_works":["https://openalex.org/W1530210183","https://openalex.org/W1990589796","https://openalex.org/W2009948657","https://openalex.org/W2053584122","https://openalex.org/W2073834924","https://openalex.org/W2094145178","https://openalex.org/W2108862644","https://openalex.org/W2115584760","https://openalex.org/W2142537246","https://openalex.org/W2143331230","https://openalex.org/W2741497758","https://openalex.org/W2911964244","https://openalex.org/W3001645704","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W2118564381","https://openalex.org/W3160516639","https://openalex.org/W2163901716","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2152204162","https://openalex.org/W2138488530","https://openalex.org/W2739821120","https://openalex.org/W25098770"],"abstract_inverted_index":{"In":[0,46],"most":[1],"existing":[2],"works,":[3],"nDCG":[4,27,60,77,97,113,123,132],"is":[5,43],"computed":[6],"for":[7],"a":[8,21,51,75,81],"fixed":[9,17],"cutoff":[10],"k,":[11],"i.e.,":[12],"[email":[13],"protected]":[14],"and":[15,42],"some":[16],"discounting":[18],"coefficient.":[19],"Such":[20],"conventional":[22,95],"query-independent":[23,96,122],"way":[24],"to":[25,71,80,138],"compute":[26],"does":[28],"not":[29],"accurately":[30],"reflect":[31],"the":[32,55,62,65,85,94,105,121,125],"utility":[33],"of":[34,54,57,64,88,108],"search":[35],"results":[36,102],"perceived":[37],"by":[38],"an":[39],"individual":[40,126],"user":[41],"thus":[44],"non-optimal.":[45],"this":[47],"paper,":[48],"we":[49],"conduct":[50],"case":[52],"study":[53],"impact":[56],"using":[58,74,93,111,120],"query-specific":[59,76,112,131],"on":[61],"choice":[63],"optimal":[66],"Learning-to-Rank":[67],"(LETOR)":[68],"methods,":[69],"particularly":[70],"see":[72],"whether":[73],"would":[78,98],"lead":[79],"different":[82,117],"conclusion":[83],"about":[84],"relative":[86,106],"performance":[87],"multiple":[89],"LETOR":[90,109],"methods":[91,110],"than":[92],"otherwise.":[99],"Our":[100],"initial":[101],"show":[103],"that":[104,130],"ranking":[107],"can":[114],"be":[115,134],"dramatically":[116],"from":[118],"those":[119],"at":[124],"query":[127],"level,":[128],"suggesting":[129],"may":[133],"useful":[135],"in":[136,143],"order":[137],"obtain":[139],"more":[140],"reliable":[141],"conclusions":[142],"retrieval":[144],"experiments.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}