{"id":"https://openalex.org/W2544513229","doi":"https://doi.org/10.1109/nlpke.2011.6138167","title":"Learning the weight of the query term from the relevance feedback","display_name":"Learning the weight of the query term from the relevance feedback","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2544513229","doi":"https://doi.org/10.1109/nlpke.2011.6138167","mag":"2544513229"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2011.6138167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","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/A5101818033","display_name":"Bingqing Wang","orcid":"https://orcid.org/0000-0001-8737-4563"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingqing Wang","raw_affiliation_strings":["Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100559702","display_name":"Yaqian Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqian Zhou","raw_affiliation_strings":["Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360407","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0003-0947-4942"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xuanjing Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanjing Huang","raw_affiliation_strings":["Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Media Computing and Web Intelligence, School of Computer Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.4738,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6574102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"43","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991999864578247,"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":0.9988999962806702,"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/computer-science","display_name":"Computer science","score":0.7769817113876343},{"id":"https://openalex.org/keywords/term-discrimination","display_name":"Term Discrimination","score":0.7224627733230591},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.657133936882019},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6266006827354431},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.6228216290473938},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.60576331615448},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.5802684426307678},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.5604655146598816},{"id":"https://openalex.org/keywords/divergence-from-randomness-model","display_name":"Divergence-from-randomness model","score":0.5600700974464417},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.526628315448761},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4931771159172058},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4902387261390686},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.47135108709335327},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.46765750646591187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43961694836616516},{"id":"https://openalex.org/keywords/concept-search","display_name":"Concept search","score":0.28233277797698975},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.27749669551849365},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.2604212760925293},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.22429129481315613},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.14707791805267334}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7769817113876343},{"id":"https://openalex.org/C22639730","wikidata":"https://www.wikidata.org/wiki/Q7702546","display_name":"Term Discrimination","level":5,"score":0.7224627733230591},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.657133936882019},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6266006827354431},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.6228216290473938},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.60576331615448},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.5802684426307678},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.5604655146598816},{"id":"https://openalex.org/C149189445","wikidata":"https://www.wikidata.org/wiki/Q5283894","display_name":"Divergence-from-randomness model","level":3,"score":0.5600700974464417},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.526628315448761},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4931771159172058},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4902387261390686},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.47135108709335327},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.46765750646591187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43961694836616516},{"id":"https://openalex.org/C182861755","wikidata":"https://www.wikidata.org/wiki/Q5158391","display_name":"Concept search","level":4,"score":0.28233277797698975},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27749669551849365},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2604212760925293},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.22429129481315613},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.14707791805267334},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2011.6138167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W1928657940","https://openalex.org/W1964348731","https://openalex.org/W1972594981","https://openalex.org/W1989885825","https://openalex.org/W1990589796","https://openalex.org/W1993691599","https://openalex.org/W2030760474","https://openalex.org/W2034117506","https://openalex.org/W2067802667","https://openalex.org/W2068905009","https://openalex.org/W2070740689","https://openalex.org/W2093390569","https://openalex.org/W2096562762","https://openalex.org/W2104049510","https://openalex.org/W2105157020","https://openalex.org/W2132800298","https://openalex.org/W2141719669","https://openalex.org/W2152314154","https://openalex.org/W2594639291","https://openalex.org/W4206765718","https://openalex.org/W4238240379","https://openalex.org/W4243333943"],"related_works":["https://openalex.org/W2326718978","https://openalex.org/W1999713929","https://openalex.org/W2351074824","https://openalex.org/W2062666034","https://openalex.org/W1924059391","https://openalex.org/W1492957152","https://openalex.org/W2364053392","https://openalex.org/W2376017636","https://openalex.org/W2096313274","https://openalex.org/W1561049396"],"abstract_inverted_index":{"We":[0,67,85],"address":[1],"the":[2,13,24,27,33,45,64,87,95,108,111,114,117,124,128,137,141,146,151,156,165,180,186,203,214],"problem":[3],"of":[4,110,206],"assigning":[5],"each":[6,82,132,196],"query":[7,28,133,197],"word":[8],"an":[9,69,210],"appropriate":[10],"weight":[11,17,54,80,126,148,194],"in":[12,116,127,179],"retrieval":[14,34,39,65,74,89,96,129],"function.":[15],"Term":[16],"assignment":[18],"is":[19,104],"important,":[20],"which":[21,47,103,171],"depends":[22],"on":[23,168,185],"relationship":[25],"among":[26],"words":[29],"and":[30,55,91,140,208],"also":[31],"impacts":[32],"performance":[35,212],"directly.":[36],"However,":[37],"various":[38],"models":[40],"can":[41,59,120,172,201],"be":[42,121,173],"adopted":[43],"by":[44,149,191],"system,":[46],"requires":[48],"different":[49,73],"approaches":[50],"to":[51,62,76,81,93,106,144,195],"set":[52,77],"term":[53,125,147],"those":[56],"empirical":[57],"settings":[58],"not":[60],"ensure":[61],"improve":[63],"quality.":[66],"propose":[68,92],"unified":[70],"approach":[71,200],"for":[72],"functions":[75,90],"a":[78,99,176],"unique":[79],"individual":[83],"word.":[84],"explore":[86],"popular":[88],"regard":[94],"function":[97],"as":[98,123,155,175],"linear":[100],"classification":[101],"model,":[102],"aimed":[105],"predicate":[107],"relevance":[109,152,169],"document.":[112],"Thus":[113],"parameters":[115],"learning":[118],"model":[119,139,143],"explained":[122],"model.":[130,182,217],"For":[131],"topic,":[134],"we":[135],"adopt":[136],"generative":[138,181],"discriminative":[142],"estimate":[145],"taking":[150],"feedback":[153],"information":[154],"training":[157],"data.":[158],"Our":[159],"analysis":[160],"gives":[161],"more":[162],"insight":[163],"into":[164],"Rocchio's":[166],"framework":[167],"feedback,":[170],"taken":[174],"special":[177],"case":[178],"Experimental":[183],"results":[184],"benchmark":[187],"datasets":[188],"show":[189],"that":[190],"estimating":[192],"proper":[193],"word,":[198],"our":[199],"outperform":[202],"baseline":[204],"methods":[205],"BM25":[207],"obtain":[209],"equivalent":[211],"with":[213],"probability":[215],"language":[216]},"counts_by_year":[{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}