{"id":"https://openalex.org/W7144188479","doi":"https://doi.org/10.20736/0002001336","title":"CIR at the NTCIR-17 ULTRE-2 Task","display_name":"CIR at the NTCIR-17 ULTRE-2 Task","publication_year":2023,"publication_date":"2023-12-12","ids":{"openalex":"https://openalex.org/W7144188479","doi":"https://doi.org/10.20736/0002001336"},"language":"en","primary_location":{"id":"pmh:oai:irdb.nii.ac.jp:03100:0005993310","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2001336","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"type":"conference-paper","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.nii.ac.jp/records/2001336","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5131101164","display_name":"Lulu Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lulu Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5131297380","display_name":"Keping Bi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keping Bi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109736354","display_name":"Jiafeng Guo","orcid":"https://orcid.org/0000-0002-9509-8674"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiafeng Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5131170010","display_name":"Xueqi Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xueqi Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"none","last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9071999788284302,"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":0.9071999788284302,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.019200000911951065,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.015399999916553497,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7045999765396118},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5997999906539917},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5888000130653381},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5809999704360962},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4350000023841858},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.3237999975681305}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7045999765396118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7010999917984009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6880999803543091},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5997999906539917},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5888000130653381},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5809999704360962},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4860000014305115},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3237999975681305},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.2815999984741211},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C78780964","wikidata":"https://www.wikidata.org/wiki/Q7233193","display_name":"Position paper","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2628999948501587}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:irdb.nii.ac.jp:03100:0005993310","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2001336","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:03100:0005993310","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2001336","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6087824106216431}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Chinese":[1],"academy":[2],"of":[3,33,144],"sciences":[4],"Information":[5],"Retrieval":[6],"team":[7],"(CIR)":[8],"has":[9,141],"participated":[10],"in":[11,36,41],"the":[12,26,31,37,56,63,78,84,91,134,151,155],"NTCIR-17":[13],"ULTRE-2":[14,27],"task.":[15,28],"This":[16],"paper":[17],"describes":[18],"our":[19,23,138],"approaches":[20],"and":[21,66,104,121,137],"reports":[22],"results":[24],"on":[25],"We":[29,82],"recognize":[30],"issue":[32],"false":[34,79],"negatives":[35,120],"Baidu":[38],"search":[39],"data":[40],"this":[42],"competition":[43],"is":[44,110,147],"very":[45],"severe,":[46],"much":[47],"more":[48],"severe":[49],"than":[50,150],"position":[51,64],"bias.":[52],"Hence,":[53],"we":[54],"adopt":[55],"Dual":[57],"Learning":[58],"Algorithm":[59],"(DLA)":[60],"to":[61,73,76],"address":[62],"bias":[65],"use":[67],"it":[68],"as":[69,118,127],"an":[70],"auxiliary":[71],"model":[72,100,135],"study":[74],"how":[75],"alleviate":[77],"negative":[80],"issue.":[81],"approach":[83],"problem":[85],"from":[86,102,112,154],"two":[87],"perspectives:":[88],"1)":[89],"correcting":[90],"labels":[92],"for":[93],"non-clicked":[94],"items":[95],"by":[96],"a":[97,106],"relevance":[98],"judgment":[99],"trained":[101],"DLA,":[103],"learn":[105],"new":[107],"ranker":[108],"that":[109,123],"initialized":[111],"DLA;":[113],"2)":[114],"including":[115],"random":[116],"documents":[117,122],"true":[119],"have":[124],"partial":[125],"matching":[126],"hard":[128],"negatives.":[129],"Both":[130],"methods":[131],"can":[132],"enhance":[133],"performance":[136],"best":[139,152],"method":[140],"achieved":[142],"nDCG@10":[143],"0.5355,":[145],"which":[146],"2.66%":[148],"better":[149],"score":[153],"organizer.":[156]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-01T00:00:00"}
