{"id":"https://openalex.org/W1588290110","doi":"https://doi.org/10.1007/978-3-642-15431-7_18","title":"A Relative Word-Frequency Based Method for Relevance Feedback","display_name":"A Relative Word-Frequency Based Method for Relevance Feedback","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1588290110","doi":"https://doi.org/10.1007/978-3-642-15431-7_18","mag":"1588290110"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-15431-7_18","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"book series"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"book-chapter","type_crossref":"book-chapter","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/A5101757449","display_name":"Zilong Chen","orcid":"https://orcid.org/0000-0002-2977-1824"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilong Chen","raw_affiliation_strings":["State Key Lab. of Software Development Environment, BeiHang University, HaiDian District, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Lab. of Software Development Environment, BeiHang University, HaiDian District, Beijing, P.R. China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079130579","display_name":"Lu Yang","orcid":"https://orcid.org/0000-0003-3857-3982"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Lu","raw_affiliation_strings":["School of Software and Microelectronics, Peking University, HaiDian District, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Software and Microelectronics, Peking University, HaiDian District, Beijing, P.R. China","institution_ids":["https://openalex.org/I20231570"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392,"provenance":"doaj"},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":64},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"180"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval Techniques and Evaluation","score":0.9996,"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 Techniques and Evaluation","score":0.9996,"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/T10028","display_name":"Natural Language Processing","score":0.998,"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"}},{"id":"https://openalex.org/T10824","display_name":"Shape Matching and Object Recognition","score":0.9969,"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/relevance","display_name":"Relevance (law)","score":0.76620495},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance Feedback","score":0.626984},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.6190681},{"id":"https://openalex.org/keywords/semantic-relevance","display_name":"Semantic Relevance","score":0.587094},{"id":"https://openalex.org/keywords/word-representation","display_name":"Word Representation","score":0.563645},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information Retrieval","score":0.556514},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to Rank","score":0.543742},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47088417},{"id":"https://openalex.org/keywords/frequency","display_name":"Frequency","score":0.42770928},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4225191}],"concepts":[{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.89623785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.88258755},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.76620495},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6860347},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.6757107},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.6190681},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6127164},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.570569},{"id":"https://openalex.org/C175293574","wikidata":"https://www.wikidata.org/wiki/Q697133","display_name":"Word lists by frequency","level":3,"score":0.5134193},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47088417},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.44628096},{"id":"https://openalex.org/C199075045","wikidata":"https://www.wikidata.org/wiki/Q762856","display_name":"Frequency","level":2,"score":0.42770928},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4225191},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3843501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38004035},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.14126995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06978786},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-15431-7_18","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"book series"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.68,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":14,"referenced_works":["https://openalex.org/W1956559956","https://openalex.org/W1964348731","https://openalex.org/W2065096648","https://openalex.org/W2095368471","https://openalex.org/W2104049510","https://openalex.org/W2105378642","https://openalex.org/W2128834557","https://openalex.org/W2131784531","https://openalex.org/W2138932367","https://openalex.org/W2158976269","https://openalex.org/W2164547069","https://openalex.org/W2169213601","https://openalex.org/W2325227998","https://openalex.org/W4246858749"],"related_works":["https://openalex.org/W4234076403","https://openalex.org/W3010113995","https://openalex.org/W2577784223","https://openalex.org/W2382153208","https://openalex.org/W2364053392","https://openalex.org/W2230616111","https://openalex.org/W2027155619","https://openalex.org/W1561049396","https://openalex.org/W1555107002","https://openalex.org/W1160915619"],"abstract_inverted_index":{"Traditional":[0],"relevance":[1,113,165],"feedback":[2,114,166],"methods,":[3],"which":[4],"usually":[5],"use":[6],"the":[7,12,20,43,49,59,96,104,121,144,153],"most":[8],"frequent":[9],"terms":[10,17,34,93],"in":[11,30,36,71],"relevant":[13,82],"documents":[14,83],"as":[15],"expansion":[16,33,65,92],"to":[18,42,48,62,95,102],"enrich":[19],"user\u2019s":[21],"initial":[22,105],"query,":[23],"could":[24],"help":[25,80],"improve":[26],"retrieval":[27,137],"performance.":[28],"However,":[29],"reality,":[31],"many":[32],"identified":[35],"traditional":[37,164],"approaches":[38],"are":[39],"indeed":[40],"unrelated":[41],"query":[44],"and":[45,78,99,126],"even":[46],"harmful":[47],"retrieval.":[50],"This":[51],"paper":[52,73],"introduces":[53],"a":[54,75,109],"new":[55,76,88],"method":[56],"based":[57],"on":[58,131],"relative":[60,68,97],"word-frequency":[61,69,98],"select":[63],"good":[64,91],"terms.":[66],"The":[67,87],"defined":[70],"this":[72],"is":[74,147,159],"feature":[77],"can":[79,139],"discriminate":[81],"from":[84],"irrelevant":[85],"ones.":[86],"approach":[89,146,158],"selects":[90],"according":[94],"uses":[100],"them":[101],"reformulate":[103],"query.":[106],"We":[107],"compare":[108],"set":[110],"of":[111,155],"existing":[112],"methods":[115],"with":[116],"our":[117,156],"proposed":[118,145,157],"approach,":[119],"including":[120],"representative":[122],"vector":[123],"space":[124],"models":[125],"language":[127],"models.":[128],"Our":[129],"experiments":[130],"several":[132],"TREC":[133],"collections":[134],"demonstrate":[135],"that":[136,152],"effectiveness":[138],"be":[140],"much":[141],"improved":[142],"when":[143],"used.":[148],"Experimental":[149],"results":[150],"show":[151],"improvement":[154],"more":[160],"than":[161],"30%":[162],"over":[163],"techniques.":[167]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1588290110","counts_by_year":[],"updated_date":"2024-09-24T04:31:25.480012","created_date":"2016-06-24"}