{"id":"https://openalex.org/W1976758266","doi":"https://doi.org/10.1145/2124295.2124338","title":"Extracting search-focused key n-grams for relevance ranking in web search","display_name":"Extracting search-focused key n-grams for relevance ranking in web search","publication_year":2012,"publication_date":"2012-02-08","ids":{"openalex":"https://openalex.org/W1976758266","doi":"https://doi.org/10.1145/2124295.2124338","mag":"1976758266"},"language":"en","primary_location":{"id":"doi:10.1145/2124295.2124338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2124295.2124338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the fifth ACM international conference on Web search and data mining","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/A5100337506","display_name":"Chen Wang","orcid":"https://orcid.org/0000-0001-8193-3619"},"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":true,"raw_author_name":"Chen Wang","raw_affiliation_strings":["Fudan University, Shanghai, China","Fudan University Shanghai, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Fudan University Shanghai, China#TAB#","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040708820","display_name":"Keping Bi","orcid":"https://orcid.org/0000-0001-5123-4999"},"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":"Keping Bi","raw_affiliation_strings":["Peking University, Beijing, China","Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110380262","display_name":"Yunhua Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhua Hu","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455135","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-3464-3245"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110660237","display_name":"Guihong Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guihong Cao","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100337506"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":4.4038,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94348744,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"343","last_page":"352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9980999827384949,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9980999827384949,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9970999956130981,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9965000152587891,"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/ranking","display_name":"Ranking (information retrieval)","score":0.7987802028656006},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7778042554855347},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.7722563743591309},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.7680327296257019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7479497790336609},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.7472133636474609},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5609884262084961},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.5539216995239258},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.5444428324699402},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.436376690864563},{"id":"https://openalex.org/keywords/web-search-engine","display_name":"Web search engine","score":0.43252187967300415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34323424100875854},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.3374263048171997},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.26708734035491943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1429750919342041}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7987802028656006},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7778042554855347},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.7722563743591309},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.7680327296257019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7479497790336609},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.7472133636474609},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5609884262084961},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.5539216995239258},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.5444428324699402},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.436376690864563},{"id":"https://openalex.org/C521815418","wikidata":"https://www.wikidata.org/wiki/Q4182287","display_name":"Web search engine","level":4,"score":0.43252187967300415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34323424100875854},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.3374263048171997},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.26708734035491943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1429750919342041},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2124295.2124338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2124295.2124338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the fifth ACM international conference on Web search and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.225.3626","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.3626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/en-us/people/hangli/wsdm030-wang.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W135190683","https://openalex.org/W179016587","https://openalex.org/W1549656520","https://openalex.org/W1559743959","https://openalex.org/W1907578970","https://openalex.org/W1973435495","https://openalex.org/W1985554184","https://openalex.org/W2009077327","https://openalex.org/W2014415866","https://openalex.org/W2015441003","https://openalex.org/W2035720976","https://openalex.org/W2037140704","https://openalex.org/W2047221353","https://openalex.org/W2051082414","https://openalex.org/W2060772621","https://openalex.org/W2062270497","https://openalex.org/W2064418625","https://openalex.org/W2068905009","https://openalex.org/W2070740689","https://openalex.org/W2093390569","https://openalex.org/W2097385711","https://openalex.org/W2097443371","https://openalex.org/W2103971611","https://openalex.org/W2105008421","https://openalex.org/W2125771191","https://openalex.org/W2126482906","https://openalex.org/W2134131174","https://openalex.org/W2145076056","https://openalex.org/W2145766604","https://openalex.org/W2148117599","https://openalex.org/W2149427297","https://openalex.org/W2149469409","https://openalex.org/W2164067199","https://openalex.org/W2165612380","https://openalex.org/W2166954187","https://openalex.org/W2988119488","https://openalex.org/W4206765718","https://openalex.org/W4243333943","https://openalex.org/W4245107743","https://openalex.org/W4251560691","https://openalex.org/W7043762925"],"related_works":["https://openalex.org/W85699040","https://openalex.org/W2986119073","https://openalex.org/W3127142483","https://openalex.org/W2128281062","https://openalex.org/W2114531539","https://openalex.org/W2125398996","https://openalex.org/W2142697503","https://openalex.org/W4391549777","https://openalex.org/W4385489465","https://openalex.org/W2142537246"],"abstract_inverted_index":{"In":[0,26,43],"web":[1,74,212],"search,":[2],"relevance":[3,32,192,224],"ranking":[4,33,193,225],"of":[5,12,15,41,83,93,158,190,206,240],"popular":[6,30],"pages":[7],"is":[8,48],"relatively":[9],"easy,":[10],"because":[11],"the":[13,46,55,61,78,84,87,91,114,129,156,162,168,174,179,182,191,204,207],"inclusion":[14],"strong":[16],"signals":[17],"such":[18,154],"as":[19,51,120,188],"anchor":[20],"text":[21],"and":[22,54,76,230,232],"search":[23,151,163,213],"log":[24,152,164],"data.":[25],"contrast,":[27],"with":[28,197,210,236],"less":[29],"pages,":[31,53,75,85],"becomes":[34],"very":[35],"challenging":[36],"due":[37],"to":[38,50,142,173,178,199],"a":[39,65,137],"lack":[40],"information.":[42],"this":[44,96],"paper":[45],"former":[47],"referred":[49],"head":[52],"latter":[56],"tail":[57,88],"pages.":[58,89],"We":[59],"address":[60],"challenge":[62],"by":[63],"learning":[64,141,198],"model":[66,194],"that":[67,116,155,218],"can":[68,123,170,221],"extract":[69],"search-focused":[70,112],"key":[71,79,109,132,146,159,184],"n-grams":[72,80,110,133,147,160,185],"from":[73],"using":[77,140,150],"for":[81,127],"searches":[82],"particularly,":[86],"To":[90],"best":[92],"our":[94,219,241],"knowledge,":[95],"problem":[97],"has":[98,105],"not":[99],"been":[100,245],"previously":[101],"studied.":[102],"Our":[103],"approach":[104,209,220,242],"four":[106],"characteristics.":[107],"First,":[108],"are":[111,118,134,148,186],"in":[113,136,161,167],"sense":[115,139],"they":[117],"defined":[119],"those":[121],"which":[122],"compose":[124],"\"good":[125],"queries\"":[126],"searching":[128],"page.":[130],"Second,":[131],"learned":[135,149],"relative":[138],"rank":[143,200],"techniques.":[144,201],"Third,":[145],"data,":[153,165,176],"characteristics":[157],"particularly":[166,177,233],"heads;":[169],"be":[171],"applied":[172],"other":[175],"tails.":[180],"Fourth,":[181],"extracted":[183],"used":[187],"features":[189],"also":[195,244],"trained":[196],"Experiments":[202],"validate":[203],"effectiveness":[205],"proposed":[208],"large-scale":[211],"datasets.":[214],"The":[215],"results":[216],"show":[217],"significantly":[222],"improve":[223],"performance":[226],"on":[227],"both":[228],"heads":[229],"tails;":[231],"tails,":[234],"compared":[235],"baseline":[237],"approaches.":[238],"Characteristics":[239],"have":[243],"fully":[246],"investigated":[247],"through":[248],"comprehensive":[249],"experiments.":[250]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
