Pat Langley Institute for the Study of Learning and Expertise Palo Alto, California and

Pat LangleyPat Langley

Institute for the Study of Learning and ExpertiseInstitute for the Study of Learning and ExpertisePalo Alto, CaliforniaPalo Alto, California

andandCenter for the Study of Language and Center for the Study of Language and

InformationInformationStanford University, Stanford, CaliforniaStanford University, Stanford, California

http://cll.stanford.edu/~langleyhttp://cll.stanford.edu/~langley

langley@csli.stanford.edulangley@csli.stanford.edu

Adaptive User InterfacesAdaptive User Interfacesfor Personalized Servicesfor Personalized Services

Thanks to D. Billsus, M. Chen, C.-N. Fiechter, M. Gervasio, M. Goker, W. Iba, S. Rogers,Thanks to D. Billsus, M. Chen, C.-N. Fiechter, M. Gervasio, M. Goker, W. Iba, S. Rogers,C. Thompson, and J. Yoo. C. Thompson, and J. Yoo.

We now have more information and choices available than We now have more information and choices available than ever before, and we need help to handle them effectively. ever before, and we need help to handle them effectively.

The Need for Personalized AssistanceThe Need for Personalized Assistance

This has led to This has led to recommendation systemsrecommendation systems, which , which help users locate and select relevant items.help users locate and select relevant items.

But often we want But often we want personalizedpersonalized assistance that assistance that takes into account our individual preferences. takes into account our individual preferences.

However, such personalized response requires a user However, such personalized response requires a user modelmodel or or profile profile that is constructed in some manner.that is constructed in some manner.

Approaches to User ModelingApproaches to User Modeling

Hand-craftedHand-craftedProfilesProfiles

Adaptive UserAdaptive UserInterfacesInterfaces

Data-MiningData-MiningMethodsMethods

Hand-craftedHand-craftedStereotypesStereotypes

IndividualIndividualProfilesProfiles

StereotypicalStereotypicalProfilesProfiles

ManualManualConstructionConstruction

AutomatedAutomatedConstructionConstruction

Definition of an Adaptive User InterfaceDefinition of an Adaptive User Interface

that reducesuser effort

by acquiringa user model

based on pastuser interaction

a softwareartifact

Definition of a Machine Learning SystemDefinition of a Machine Learning System

that improvestask performance

by acquiringknowledge

based on partialtask experience

a softwareartifact

Applications of Adaptive User InterfacesApplications of Adaptive User Interfaces

Web browsingWeb browsing

TV selectionTV selection

bookbookselectionselection

in-carin-carnavigationnavigation

apartmentapartmentselectionselection

Email filingEmail filing

news filteringnews filtering interactiveinteractiveschedulingscheduling

stockstocktrackingtracking

Inferring Individual User ProfilesInferring Individual User Profiles

Our work focuses on Our work focuses on content-basedcontent-based approaches to adaptive user approaches to adaptive user interfaces, rather than on interfaces, rather than on collaborativecollaborative approaches. approaches.

Tasks that requireTasks that require a user decisiona user decision

A descriptionA descriptionfor each taskfor each task

Traces of theTraces of theuser’s decisionsuser’s decisions

Mapping from taskMapping from taskfeatures ontofeatures ontouser decisionsuser decisions

FindFind

Navigation aides already exist in both vehicles and on the World Navigation aides already exist in both vehicles and on the World Wide Web.Wide Web.

One decision-making task that confronts drivers can be stated One decision-making task that confronts drivers can be stated as:as:

However, they do not give However, they do not give personalizedpersonalized navigation advice to navigation advice to individual drivers.individual drivers.

• Given: Given: The driver’s current location The driver’s current location C;C;• Given: Given: The destination The destination DD that the driver desires; that the driver desires;• Given: Given: Knowledge about available roads (e.g., a digital map); Knowledge about available roads (e.g., a digital map); • Find: Find: One or more desirable routes from One or more desirable routes from CC to to D.D.

The Task of Route SelectionThe Task of Route Selection

The Adaptive Route AdvisorThe Adaptive Route Advisor

The Adaptive Route Advisor represents the driver model as a The Adaptive Route Advisor represents the driver model as a weighted linear combination of route features. weighted linear combination of route features.

Training cases: [x0, . . . , xn] is better than [y0, . . . , yn].Training cases: [x0, . . . , xn] is better than [y0, . . . , yn].

TimeTimeDistanceDistance

IntersectionsIntersectionsTurnsTurns

CostCostw0w1w2w3

Generating Training CasesGenerating Training Cases

The system uses each training pair as constraints on the weights The system uses each training pair as constraints on the weights found during the modeling process.found during the modeling process.

Personalized user models produce better results than generalized Personalized user models produce better results than generalized models, even when the latter are based on more data. models, even when the latter are based on more data.

Experimental Results on Route AdviceExperimental Results on Route Advice

Many online news services are available on the World Wide Many online news services are available on the World Wide Web, but few offer personalized selection.Web, but few offer personalized selection.

Another service that would benefit drivers can be stated as:Another service that would benefit drivers can be stated as:

Moreover, they are ill suited for use in the driving environment, Moreover, they are ill suited for use in the driving environment, where visual attention is a limited resource. where visual attention is a limited resource.

• Given: Given: Topics and events that interest the driver; Topics and events that interest the driver; • Given: Given: Recent news stories available on the Web;Recent news stories available on the Web;• Given: Given: Knowledge about stories the driver has heard; Knowledge about stories the driver has heard; • Find: Find: Stories to read the driver during the current tripStories to read the driver during the current trip..

The Task of News ReadingThe Task of News Reading

News Dude (Billsus & Pazzani, 1999)News Dude (Billsus & Pazzani, 1999)

Adaptive News Readers in the MarketplaceAdaptive News Readers in the Marketplace

Many recommendation systems are available on the World Wide Many recommendation systems are available on the World Wide Web, including ones that suggest restaurants.Web, including ones that suggest restaurants.

A third type of service that would assist drivers can be stated as:A third type of service that would assist drivers can be stated as:

However, they are not designed for use by drivers, who must However, they are not designed for use by drivers, who must keep their eyes on the road. keep their eyes on the road.

• Given: Given: Some goal the driver wants to achieve (e.g., eat lunch);Some goal the driver wants to achieve (e.g., eat lunch);• Given: Given: Constraints on destinations that achieve this goal; Constraints on destinations that achieve this goal; • Given: Given: Knowledge about available nearby destinations; Knowledge about available nearby destinations; • Find: Find: One or more destinations that satisfy the constraintsOne or more destinations that satisfy the constraints..

The Task of Destination SelectionThe Task of Destination Selection

The Adaptive Place AdvisorThe Adaptive Place Advisor

Results,Attribute Information

User Operatorsand Values

System Operatorsand Values

Dialogue Manager

Speech Generator Speech Recognizer

User ModelingSystem

RecognitionGrammarsPrompts

ItemDatabase

UserModels

Conversation History Updated QueryInitial Query

Retrieval Engine

System Output(Voice)

User Input(Voice)

DomainModel

Inquirer:Inquirer: Where do you think I should eat tonight? Where do you think I should eat tonight?

Advisor: What type of food would you like?Advisor: What type of food would you like?

Inquirer:Inquirer: What types are there? What types are there?

Advisor: You can say things like Chinese, Indian, and Advisor: You can say things like Chinese, Indian, and Mediterranean.Mediterranean.

Inquirer:Inquirer: Oh, maybe a French place with free parking. Oh, maybe a French place with free parking.

Advisor: What quality rating would you like?Advisor: What quality rating would you like?

Inquirer:Inquirer: I don't care, as long as it's cheap. I don't care, as long as it's cheap.

Advisor: I’m sorry, I don’t know any restaurants like that. Advisor: I’m sorry, I don’t know any restaurants like that. Would you like to search for any price?Would you like to search for any price?

Inquirer:Inquirer: No, I think I'd like Chinese instead. No, I think I'd like Chinese instead.

Advisor: In what city would you like to eat?Advisor: In what city would you like to eat?

Inquirer:Inquirer: How about Berkeley? How about Berkeley?

Advisor:Advisor: How does the Long Life Vegi House on 2129 University How does the Long Life Vegi House on 2129 University Avenue sound?Avenue sound?

Inquirer:Inquirer: Sure, that sounds fine.Sure, that sounds fine.

Adaptive Place Advisor (Before Adaptation)Adaptive Place Advisor (Before Adaptation)

Inquirer:Inquirer: Where do you think I should eat tonight? Where do you think I should eat tonight?

Advisor: What type of food would you like?Advisor: What type of food would you like?

Inquirer:Inquirer: Cheap Chinese. Cheap Chinese.

Advisor: Advisor: What city do you prefer? What city do you prefer?

Inquirer: How about Palo Alto? Inquirer: How about Palo Alto?

Advisor: How does Jing Jing Szechuan Gourmet Advisor: How does Jing Jing Szechuan Gourmet on 443 Emerson sound?on 443 Emerson sound?

Inquirer:Inquirer: Sure, that sounds fine.Sure, that sounds fine.

Adaptive Place Advisor (After Adaptation)Adaptive Place Advisor (After Adaptation)

Speech Acts Per ConversationSpeech Acts Per Conversationwith Adaptive Place Advisorwith Adaptive Place Advisor

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

dialogue number

num

ber o

f spe

ech

acts

modeling

control

INCA: An Adaptive SchedulerINCA: An Adaptive Scheduler

BackFlip: Personalized BookmarkingBackFlip: Personalized Bookmarking

Personalized Music DeliveryPersonalized Music Delivery

A Personalized Travel AgentA Personalized Travel Agent

An Adaptive Apartment FinderAn Adaptive Apartment Finder

An Adaptive Stock TrackerAn Adaptive Stock Tracker

Alternative Presentation StylesAlternative Presentation StylesSe

quen

tial

Sequ

entia

l

Cla

ssifi

catio

nC

lass

ifica

tion

Twea

ked

Set

Twea

ked

Set

Ran

ked

List

Ran

ked

List

suggestinitialize

short-termprofile

initialize/retrieveprofile

specifyquery

modify

present

respond

decideDecision

Long-termprofile

Item database

User query

Suggestion User

Response

Updateprofile

Short-termprofile

A Flexible Framework for Adaptive InterfacesA Flexible Framework for Adaptive Interfaces

Challenges in Developing an Adaptive InterfaceChallenges in Developing an Adaptive Interface

Formulatingthe Problem

Engineering theRepresentation

CollectingUser Traces

Utilizing ModelEffectively

Gaining UserAcceptance

ModelingProcess

Contributions of the ResearchContributions of the Research

Our research program on adaptive user interfaces has produced: Our research program on adaptive user interfaces has produced:

Although some issues remain, we understand adaptive interfaces Although some issues remain, we understand adaptive interfaces well enough to apply them in practical services. well enough to apply them in practical services.

• a variety of artifacts that learn user preferences unobtrusively;a variety of artifacts that learn user preferences unobtrusively;

• evidence that this approach to user modeling is a general one;evidence that this approach to user modeling is a general one;

• experimental support for the effectiveness of these systems;experimental support for the effectiveness of these systems;

• an analysis of presentation styles possible for such systems;an analysis of presentation styles possible for such systems;

• a flexible framework for constructing them efficiently; anda flexible framework for constructing them efficiently; and

• clarification of issues that arise in their effective design.clarification of issues that arise in their effective design.

Directions for Future ResearchDirections for Future Research

Despite clear progress on adaptive user interfaces, we must still:Despite clear progress on adaptive user interfaces, we must still:

Together, these advances will lead us toward a society in which Together, these advances will lead us toward a society in which personalized computational aides are a regular part of our lives. personalized computational aides are a regular part of our lives.

• design methods to combine stereotypes and individual profiles;design methods to combine stereotypes and individual profiles;

• create approaches that transfer user profiles across domains;create approaches that transfer user profiles across domains;

• apply these techniques to an ever wider range of problems;apply these techniques to an ever wider range of problems;

• utilize new sensors to collect data even less obtrusively; andutilize new sensors to collect data even less obtrusively; and

• develop complete physical environments that adapt to users.develop complete physical environments that adapt to users.

Dialogue Operators for Adaptive Place AdvisorDialogue Operators for Adaptive Place Advisor

System OperatorsSystem OperatorsAsk-ConstrainAsk-Constrain Asks a question to obtain a value for an attributeAsks a question to obtain a value for an attributeAsk-RelaxAsk-Relax Asks a question to remove a value of an attributeAsks a question to remove a value of an attributeSuggest-ValuesSuggest-Values Suggests a small set of possible values for an attributeSuggests a small set of possible values for an attributeSuggest-AttributesSuggest-Attributes Suggests a small set of unconstrained attributes Suggests a small set of unconstrained attributes Recommend-ItemRecommend-Item Recommends an item that satisfies the current constraintsRecommends an item that satisfies the current constraintsClarifyClarify Asks a clarifying question if uncertain about latest user operatorAsks a clarifying question if uncertain about latest user operator

User OperatorsUser OperatorsProvide-ConstrainProvide-Constrain Provides a value for an attributeProvides a value for an attributeReject-ConstrainReject-Constrain Rejects the proposed attributeRejects the proposed attributeAccept-RelaxAccept-Relax Accepts the removal of an attribute valueAccepts the removal of an attribute valueReject-RelaxReject-Relax Rejects the removal of an attribute valueRejects the removal of an attribute valueAccept-ItemAccept-Item Accepts the proposed item Accepts the proposed item Reject-ItemReject-Item Rejects the proposed itemRejects the proposed itemQuery-AttributesQuery-Attributes Asks system for information about possible attributesAsks system for information about possible attributesQuery-ValuesQuery-Values Asks system for information about possible attribute valuesAsks system for information about possible attribute valuesStart-OverStart-Over Asks the system to re-initialize the searchAsks the system to re-initialize the searchQuitQuit Asks the system to abort the searchAsks the system to abort the search