基于大規(guī)模行為數(shù)據(jù)的用戶畫像課件

1、基于大規(guī)模行為數(shù)據(jù)的用戶畫像用戶大數(shù)據(jù)2用戶畫像用戶畫像DemographicAgeGenderLife stageMarital statusResidenceEducationVocationPersonalityOpennessConscientiousnessExtraversionAgreeablenessNeuroticismImpulsivityNovelty-seekingIndecisiveness InterestsFoodBookMovieMusicSportRestaurantStatusEmotionEventHealthWealthDeviceSocialFrien

2、dCoworkerSpouseChildrenOther relativesTie strengthScheduleTaskDriving routeMetro/bus lineAppointmentVacation相關(guān)研究工作Dynamics of Online IntimacyWSDM 2016Location to ProfileWSDM 2015Big Five PersonalityWSDM 2017Location InterestsIJCAI 2017Consumer ImpulsivityUbiComp 2015Novelty SeekingTraitWWW 2015/WWW

3、2014LifeSpec跨平臺用戶行為數(shù)據(jù)集6LifeSpec跨平臺用戶行為數(shù)據(jù)集Average bedtime of different cities(1M respondents, led by Chinese Medical Doctor Association, announced in world sleep day 2013) BeijingGuangzhouRankCityBedtime7用戶移動規(guī)律與位置預(yù)測8基于用戶位置數(shù)據(jù)的用戶畫像GenderEducationMarital StatusZodiac SignAgeLocation check-ins of Beijing

4、 and ShanghaiLocation to Profile (L2P) Framework SpatialityTemporality Location KnowledgeUsers demographics用戶移動規(guī)律RestrictionTemporal & Spatial RegularityM. C. Gonzalez, C. A. Hidalgo, and A.-L. Barabasi. Understanding individual human mobility patterns. Nature, 453 (7196):779782, 2008.Song C, Qu Z,

5、Blumm N, et al. Limits of predictability in human mobilityJ. Science, 2010, 327(5968): 1018-1021.基于用戶位置數(shù)據(jù)的用戶畫像四體液說黑色的膽汁產(chǎn)生了憂郁型人格血液產(chǎn)生了樂觀型人格黃色的膽汁產(chǎn)生了易怒型人格粘液產(chǎn)生了冷靜型人格詞匯學(xué)假說在人們生活中，最重要的那些人格特質(zhì)最終會成為語言的一部分。 相對重要的人格特質(zhì)更可能以一個單詞的形式，被納入語言。最初，描述人格特質(zhì)的詞匯有4500多個：“talkative”（健談）, “aggressive”（有攻擊性）, “fearful”（充滿畏懼）用戶大五人格推測外向性隨和性神經(jīng)質(zhì)盡責(zé)性開放性用戶大五人格推測用戶文字與大五人格ExtraversionAgreeablenessNeuroticismConscientiousnessOpennessPositiveNegative用戶頭像與大五人格ExtraversionAgreeablenessNeuroticismConscientiousnessOpennessPositiveNegative非你莫屬節(jié)目助理主持人更像人的聊天機器人隨著帶有用戶標(biāo)簽的語言數(shù)據(jù)變得容易獲取，如果我們有足夠的關(guān)于某個人的數(shù)據(jù)，就能訓(xùn)練出一個和他個性一樣的聊天機器人我們還可以通過一群人，例如兒童、