PersonalizationPersonalization

Speaker: Ping-Tsun ChangSpeaker: Ping-Tsun Chang

3/7/20023/7/2002

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||)||)

Yahoo!