{"id":"https://openalex.org/W2109677301","doi":"https://doi.org/10.1145/1935826.1935848","title":"Understanding and predicting personal navigation","display_name":"Understanding and predicting personal navigation","publication_year":2011,"publication_date":"2011-02-01","ids":{"openalex":"https://openalex.org/W2109677301","doi":"https://doi.org/10.1145/1935826.1935848","mag":"2109677301"},"language":"en","primary_location":{"id":"doi:10.1145/1935826.1935848","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1935826.1935848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the fourth 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/A5032417423","display_name":"Jaime Teevan","orcid":"https://orcid.org/0000-0002-2786-0209"},"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":true,"raw_author_name":"Jaime Teevan","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059138163","display_name":"Daniel J. Liebling","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":"Daniel J. Liebling","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072449290","display_name":"Gayathri Ravichandran Geetha","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":"Gayathri Ravichandran Geetha","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":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032417423"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":14.513,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.98599696,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"85","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9993000030517578,"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/T12016","display_name":"Web Data Mining and Analysis","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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9991000294685364,"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/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/personalization","display_name":"Personalization","score":0.8026824593544006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8000155687332153},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6823811531066895},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5688204765319824},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5388166308403015},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.48185694217681885},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.45083510875701904},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.42659056186676025},{"id":"https://openalex.org/keywords/web-navigation","display_name":"Web navigation","score":0.4244895875453949},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.32556432485580444},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3207654058933258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20508670806884766}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.8026824593544006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8000155687332153},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6823811531066895},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5688204765319824},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5388166308403015},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.48185694217681885},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.45083510875701904},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.42659056186676025},{"id":"https://openalex.org/C61096286","wikidata":"https://www.wikidata.org/wiki/Q7978592","display_name":"Web navigation","level":3,"score":0.4244895875453949},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.32556432485580444},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3207654058933258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20508670806884766},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1935826.1935848","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1935826.1935848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the fourth ACM international conference on Web search and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.947.4329","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.947.4329","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/pubs/142490/wsdm11-pnav.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1484330506","https://openalex.org/W1484629748","https://openalex.org/W1599547017","https://openalex.org/W1602389404","https://openalex.org/W1979030548","https://openalex.org/W1979182316","https://openalex.org/W2007572058","https://openalex.org/W2009202693","https://openalex.org/W2010463775","https://openalex.org/W2018374253","https://openalex.org/W2065222494","https://openalex.org/W2082130842","https://openalex.org/W2095976990","https://openalex.org/W2099768249","https://openalex.org/W2103399427","https://openalex.org/W2104217798","https://openalex.org/W2105612560","https://openalex.org/W2108168165","https://openalex.org/W2108566279","https://openalex.org/W2113537486","https://openalex.org/W2122841972","https://openalex.org/W2124658502","https://openalex.org/W2130196654","https://openalex.org/W2136814520","https://openalex.org/W2139873966","https://openalex.org/W2140188249","https://openalex.org/W2147823173","https://openalex.org/W2151172507","https://openalex.org/W2152314154","https://openalex.org/W2156037541","https://openalex.org/W2168717408"],"related_works":["https://openalex.org/W2116655434","https://openalex.org/W2533706070","https://openalex.org/W1541158057","https://openalex.org/W2017818230","https://openalex.org/W2268257560","https://openalex.org/W2626548695","https://openalex.org/W2184474188","https://openalex.org/W1519586109","https://openalex.org/W2030268420","https://openalex.org/W2548348270"],"abstract_inverted_index":{"This":[0,122],"paper":[1],"presents":[2],"an":[3,55,143],"algorithm":[4],"that":[5,35,41],"predicts":[6],"with":[7,86],"very":[8],"high":[9],"accuracy":[10,159],"which":[11],"Web":[12,24],"search":[13,45],"result":[14],"a":[15,30,105],"user":[16,92],"will":[17],"click":[18],"for":[19,103,126],"one":[20],"sixth":[21],"of":[22,33,38,83,107,129,138,145,163,171],"all":[23],"queries.":[25],"Prediction":[26],"is":[27,60,123],"done":[28],"via":[29,62],"straightforward":[31],"form":[32],"personalization":[34],"takes":[36],"advantage":[37,162],"the":[39,75,80,114],"fact":[40],"people":[42,111],"often":[43,112],"use":[44,113],"engines":[46],"to":[47,68,117,119,154],"re-find":[48],"previously":[49],"viewed":[50],"resources.":[51,121],"In":[52],"our":[53],"approach,":[54],"individual's":[56],"past":[57],"navigational":[58,72,96,108],"behavior":[59,73,97],"identified":[61,89],"query":[63],"log":[64],"analysis":[65],"and":[66,135,151,158,168],"used":[67],"forecast":[69],"identical":[70],"future":[71],"by":[74,160],"same":[76,115],"individual.":[77],"We":[78,141],"compare":[79],"potential":[81],"value":[82],"personal":[84,147],"navigation":[85,88,148],"general":[87],"using":[90],"aggregate":[91],"behavior.":[93],"Although":[94],"consistent":[95],"across":[98,169],"users":[99],"can":[100],"be":[101],"useful":[102],"identifying":[104],"subset":[106],"queries,":[109],"different":[110,120],"queries":[116,127],"navigate":[118],"true":[124],"even":[125],"comprised":[128],"unambiguous":[130],"company":[131],"names":[132],"or":[133],"URLs":[134],"typically":[136],"thought":[137],"as":[139],"navigational.":[140],"build":[142],"understanding":[144],"what":[146],"looks":[149],"like,":[150],"identify":[152],"ways":[153],"improve":[155],"its":[156],"coverage":[157],"taking":[161],"people's":[164],"consistency":[165],"over":[166],"time":[167],"groups":[170],"individuals.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}