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Personalization. Speaker: Ping-Tsun Chang 3/7/2002. Personalization of WWW10. Designing Personalized Web Applications Session: Personalization in E-Commerce Gustavo Rossi, Daniel Schwabe, Robson Guimaraes, Dept. of Informatics, PUC-Rio , Brazil. Personalizing Web Sites for Mobile Users - PowerPoint PPT Presentation
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Personalization of WWW10Personalization of WWW10
Designing Personalized Web ApplicationsDesigning Personalized Web ApplicationsSession: Personalization in E-Commerce Session: Personalization in E-Commerce Gustavo Rossi, Daniel Schwabe, Robson Gustavo Rossi, Daniel Schwabe, Robson
Guimaraes, Dept. of Informatics, PUC-Rio , Brazil.Guimaraes, Dept. of Informatics, PUC-Rio , Brazil. Personalizing Web Sites for Mobile UsersPersonalizing Web Sites for Mobile Users
Session: Content Transformation for Mobility Session: Content Transformation for Mobility Corin R. Anderson, Pedro Domingos, Daniel S. Corin R. Anderson, Pedro Domingos, Daniel S.
Weld, Department of Computer Science, University Weld, Department of Computer Science, University of Washington.of Washington.
MotivationMotivation
Different scenrios of personalization Different scenrios of personalization covering most existing applicationscovering most existing applications
Object-Oriented Hypermedia Design Object-Oriented Hypermedia Design Method (OOHDM)Method (OOHDM)
Personalized Web applications by refining Personalized Web applications by refining views according to users’ views according to users’ profilesprofiles or or preferencespreferences
Scenrios of PersonalizationScenrios of Personalization
Link PersonalizationLink Personalization Content PersonalizationContent Personalization
Node structure customizationNode structure customization Node content customizationNode content customization
OOHDM: Conceptual ModelOOHDM: Conceptual Model
Conceptual Model for a CD storeConceptual Model for a CD store
Name: StringDescription: [String+photo]Keywords: {String}Price: RealSize: StringSection: {Section}…DeliveryTime: string
CD
Date: date
Order
Date: date
PaymentMethod
Name: String
Performer
Text: String
Comment
Name: StringAddress:…
Customer
CdDiscountRecommendation
OOHDM: Navigation ModelOOHDM: Navigation Model
Different Navigation Schemata for different Different Navigation Schemata for different profilesprofiles
Name: StringDescription: [String+photo]Keywords: {String}Price: RealSize: StringSection: {Section}…DeliveryTime: string
CD
Name: String
Performer
Text: String
Comment
Name: StringDescription: [String+photo]Keywords: {String}Price: RealSize: StringSection: {Section}…DeliveryTime: string
CD
Date: date
Order
Name: StringAddress:…
User
includes boughtByhasComment
Hot-spotsHot-spots
In the In the conceptualconceptual model model: by explicitly representing : by explicitly representing users, roles and groups and by defining algorithms users, roles and groups and by defining algorithms that implement different (business) rules for that implement different (business) rules for different users.different users.
In the In the navigationalnavigational model model: by defining completely : by defining completely different applications for each different applications for each profileprofile, by , by customizing node contents and structure and by customizing node contents and structure and by personalizing links and indexes. personalizing links and indexes.
in the in the interfaceinterface model model: by defining different : by defining different layouts according to userlayouts according to user preferences preferences or selected or selected devices. devices.
Designing Personalized ViewsDesigning Personalized Views
Link PersonalizationLink Personalization Content PersonalizationContent Personalization
Personalizing content in a nodePersonalizing content in a node
Link personalization in OOHDMLink personalization in OOHDM
Link Recommendations, user: CustomerSOURCE HomePageTARGET CD:C WHERE C belongsTo user recommendations
NODE Customer.CD FROM CD:c, user: CustomerName: StringPrice: Real [Subject.price – user C Discount ]…Comments: Anchor [Comments]
According to some data related with the user’s buying history, his category, etc.
RecommendationRecommendation
Customer
Recommend Algorithm
getRecomm
CollaborativerFiltering
getRecomm
SimpleRecommend
getRecomm
SpecialRecommend
Recommentations()Recommender getRecomm
Decoupling users from Recommendation algorithms
If we want to improve the use of recommendation algorithms, we can model the assignment of differnet algorithms to different users by using strategiesrecommender
Recommendation: ImplementRecommendation: ImplementSequence Diagram for recommendation strategies
A Link A Customer A RecommAlgorithm
recommendations
getRecomm
A Link A Customer ThirdParty Adapter
recommendations
getRecomm
ThirdParty Recomm
recommInterface
Accommodating third party products
Context PersonalizationContext PersonalizationNavigation Diagram of Conference Paper Review system scenrio
Paper by Topic
My Reviews
by Topic
by Reviewer
by Author
by Paper
Review
Reviewer
Paper
Context Specification Card
Reusing SpecificationsReusing SpecificationsExtending a Node Specification for different user profiles
NODE CD FROM CD:CName: StringPrice: Real
Node Customer.CD Extends CDDescription: ImageComments: Anchor [Comments]
Node Manager.CD Extends CDComments:Set Select text FromComment: Co Where C hasComment Co
Goal of PersonalizationGoal of Personalization
A Web Personalizer canA Web Personalizer can Make frequently-visited destinations easier to findMake frequently-visited destinations easier to find Highlight content that interests the visitorHighlight content that interests the visitor Elide uninteresting content and structureElide uninteresting content and structure
A Web site personalizer adapts the site for the A Web site personalizer adapts the site for the mobile visitor in a two-step processmobile visitor in a two-step process The personalizer The personalizer mines the access logsmines the access logs to build a model for to build a model for
each visitoreach visitor The personalizer transforms the site to maximize the The personalizer transforms the site to maximize the
expected utility for a given visitorexpected utility for a given visitor
Personalization for Mobile UsersPersonalization for Mobile Users
Problem DefinitionProblem DefinitionV={vV={v00,…v,…vmm}} as m indivial visitors as m indivial visitorsVVii=(R, D)=(R, D) a visitor is represented as his history a visitor is represented as his history
and demographicsand demographicsR=<rR=<roo,…,r,…,rtt>> requests ordered by time requests ordered by timerrii=(u=(uss, u, udd, t, c), t, c) request is the orginating request is the orginating
page, destination page, time, and clientpage, destination page, time, and clientD=(dD=(d00,…d,…dnn)) demographic information is an n- demographic information is an n-
tuple of data itemstuple of data itemsAn Evaluation Function An Evaluation Function F(W, u, v)->RF(W, u, v)->R
Web Site Model EvaluationWeb Site Model Evaluation
Expected UtilityExpected UtilityF(W, u, v) = E[UF(W, u, v) = E[Uvv(p)](p)]
E[UE[Uvv(p(pii)] = E[U)] = E[Uvv(s(si0i0)])]
The excepted utility of a screen is the sum of its The excepted utility of a screen is the sum of its intrinsic and extrinsic utilitiesintrinsic and extrinsic utilitiesE[UE[Uvv(s(sijij)] = E[IU)] = E[IUvv(s(sijij)] + E[EU)] + E[EUvv(s(sijij)])]
Extrinsic utilities measure the value of screen by Extrinsic utilities measure the value of screen by its connection to the rest of the web siteits connection to the rest of the web siteE[EUE[EUvv(s(sijij)] = P(scroll)(E[U)] = P(scroll)(E[Uvv(s(si,j+1i,j+1)]-r)]-rss) + ) + ∑∑[P(l[P(lijkijk))(E[U(E[Uvv(d(dijkijk)]-r)]-rll)])]
Intrinsic UilityIntrinsic Uility
intrinsic utility of a screen as a weighted sum of two intrinsic utility of a screen as a weighted sum of two terms, which related to how the screen’s content matches terms, which related to how the screen’s content matches the the visitor’s previously viewed content visitor’s previously viewed content how frequently the visitor viewed the screen.how frequently the visitor viewed the screen.IUIUvv(s(sijij)] = w)] = wsjm sjm . sim. simVV (T (Tij ij ) + w) + wfreq freq . freq. freqVV (S (Sij ij ))
simsimVV (T (Tij ij ) = (w) = (wTij Tij . w. wVV)/(||w)/(||wTij Tij ||. ||w||. ||wVV||)||)
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