{"id":"https://openalex.org/W2341554990","doi":"https://doi.org/10.1145/2872518.2891070","title":"Modeling Complex Clickstream Data by Stochastic Models","display_name":"Modeling Complex Clickstream Data by Stochastic Models","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2341554990","doi":"https://doi.org/10.1145/2872518.2891070","mag":"2341554990"},"language":"en","primary_location":{"id":"doi:10.1145/2872518.2891070","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2872518.2891070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion","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/A5012481026","display_name":"Choudur Lakshminarayan","orcid":"https://orcid.org/0000-0003-2571-9372"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Choudur Lakshminarayan","raw_affiliation_strings":["Hewlett-Packard Enterprises, Austin, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hewlett-Packard Enterprises, Austin, TX, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091442784","display_name":"Ram Kosuru","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ram Kosuru","raw_affiliation_strings":["Hewlett-Packard Enterprises, Austin, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hewlett-Packard Enterprises, Austin, USA","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109925930","display_name":"Meichun Hsu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meichun Hsu","raw_affiliation_strings":["Hewlett-Packard Enterprises, Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hewlett-Packard Enterprises, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210122178"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210122178"],"apc_list":null,"apc_paid":null,"fwci":1.5723,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.83504635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"879","last_page":"884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9940000176429749,"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/clickstream","display_name":"Clickstream","score":0.8072109222412109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8039120435714722},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6088250875473022},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5401979088783264},{"id":"https://openalex.org/keywords/usability","display_name":"Usability","score":0.5220308303833008},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5074531435966492},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46712806820869446},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.46000033617019653},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.44453346729278564},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.3945731520652771},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38966649770736694},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.37752994894981384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35654380917549133},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.34667089581489563},{"id":"https://openalex.org/keywords/web-navigation","display_name":"Web navigation","score":0.2669152617454529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2391936480998993},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.22896736860275269},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.15450799465179443},{"id":"https://openalex.org/keywords/web-api","display_name":"Web API","score":0.10191401839256287}],"concepts":[{"id":"https://openalex.org/C138744977","wikidata":"https://www.wikidata.org/wiki/Q5132438","display_name":"Clickstream","level":5,"score":0.8072109222412109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039120435714722},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6088250875473022},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5401979088783264},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.5220308303833008},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5074531435966492},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46712806820869446},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.46000033617019653},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.44453346729278564},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.3945731520652771},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38966649770736694},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.37752994894981384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35654380917549133},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.34667089581489563},{"id":"https://openalex.org/C61096286","wikidata":"https://www.wikidata.org/wiki/Q7978592","display_name":"Web navigation","level":3,"score":0.2669152617454529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2391936480998993},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.22896736860275269},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.15450799465179443},{"id":"https://openalex.org/C127613066","wikidata":"https://www.wikidata.org/wiki/Q557770","display_name":"Web API","level":4,"score":0.10191401839256287}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2872518.2891070","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2872518.2891070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2004607515","https://openalex.org/W2063771604","https://openalex.org/W2077806964","https://openalex.org/W2116277390","https://openalex.org/W2123511957","https://openalex.org/W2134834365","https://openalex.org/W2169240294","https://openalex.org/W2278405760","https://openalex.org/W2482173276","https://openalex.org/W2738391309"],"related_works":["https://openalex.org/W1493153155","https://openalex.org/W2789872759","https://openalex.org/W2975622968","https://openalex.org/W2334894004","https://openalex.org/W1979144454","https://openalex.org/W2212015221","https://openalex.org/W2892191716","https://openalex.org/W2015182978","https://openalex.org/W2219566846","https://openalex.org/W1593328609"],"abstract_inverted_index":{"As":[0],"the":[1,19,31,97,105,109,122,127,132,145,158],"website":[2],"is":[3,151],"a":[4,75,135,162,189],"primary":[5],"customer":[6,16],"touch-point,":[7],"millions":[8],"are":[9,199],"spent":[10],"to":[11,30,68,72,169,188],"gather":[12],"web":[13],"data":[14,22,85,186],"about":[15],"visits.":[17],"Sadly,":[18],"trove":[20],"of":[21,62,104,111,134,148,174,185,202],"and":[23,47,87,142,164],"corresponding":[24],"analytics":[25],"have":[26],"not":[27],"lived":[28],"up":[29],"promise.":[32],"Current":[33],"marketing":[34],"practice":[35],"relies":[36],"on":[37,79,138],"ambiguous":[38],"summary":[39],"statistics":[40],"or":[41],"small-sample":[42],"usability":[43],"studies.":[44],"Idiosyncratic":[45],"browsing":[46,59],"low":[48],"conversion":[49],"(browser-to-buyer)":[50],"make":[51],"modeling":[52],"hard.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"model":[58,80],"patterns":[60],"(sequence":[61],"clicks)":[63],"via":[64],"Markov":[65,106,195],"chain":[66,107,196],"theory":[67],"predict":[69,131],"users'":[70],"propensity":[71],"buy":[73],"within":[74],"session.":[76],"We":[77],"focus":[78],"complexity,":[81],"imputing":[82],"missing":[83,118],"values,":[84],"augmentation,":[86],"other":[88],"attendant":[89],"issues":[90,178],"that":[91,194],"impact":[92],"performance.":[93,171],"The":[94,172],"paper":[95],"addresses":[96],"following":[98],"aspects;":[99],"(1)":[100],"Determine":[101],"appropriate":[102],"order":[103],"(assess":[108],"influence":[110],"prior":[112],"history":[113],"in":[114,126,179],"prediction),":[115],"(2)":[116],"Impute":[117],"transitions":[119,160],"by":[120,156],"exploiting":[121,165],"inherent":[123],"link":[124,167],"structure":[125,168],"page":[128,140,159],"sequences,":[129,141],"(3)":[130],"likelihood":[133],"purchase":[136],"based":[137,197],"variable-length":[139],"(4)":[143],"Augment":[144],"training":[146],"set":[147],"buyers":[149],"(which":[150],"typically":[152],"very":[153],"small:":[154],"2%":[155],"viewing":[157],"as":[161],"graph":[163],"its":[166],"improve":[170],"cocktail":[173],"solutions":[175],"address":[176],"important":[177],"practical":[180],"digital":[181],"marketing.":[182],"Extensive":[183],"analysis":[184],"applied":[187],"large":[190],"commercial":[191],"web-site":[192],"shows":[193],"classifiers":[198],"useful":[200],"predictors":[201],"user":[203],"intent.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
