What Difference a Group What Difference a Group MakesMakes

Web-Based Recommendations for Web-Based Recommendations for Interrelated UsersInterrelated Users

Tomek LobodaTomek Loboda

Anthony Jameson and Barry SmythAnthony Jameson and Barry Smyth

Additional PapersAdditional Papers

• Adaptive Radio: Achieving Consensus Adaptive Radio: Achieving Consensus Using Negative PreferencesUsing Negative PreferencesBy By Dennis L. Chao, Justin Balthrop, Stephanie ForrestDennis L. Chao, Justin Balthrop, Stephanie ForrestIn In Proceedings of the 2005 International ACM Proceedings of the 2005 International ACM SIGGROUP Conference on Supporting Group Work, New SIGGROUP Conference on Supporting Group Work, New York, 2005.York, 2005.At At http://www.cs.unm.edu/~dlchao/papers/chao05group.pdfhttp://www.cs.unm.edu/~dlchao/papers/chao05group.pdf

• Explaining Collaborative Filtering Explaining Collaborative Filtering RecommendationsRecommendations By By Jonathan L. Herlocker, Joseph A. Konstan, and John Jonathan L. Herlocker, Joseph A. Konstan, and John RiedlRiedlIn In Proceedings of the ACM 2000 Conference on Proceedings of the ACM 2000 Conference on Computer Supported Cooperative Work, December 2-6, Computer Supported Cooperative Work, December 2-6, 2000.2000.At At http://www.grouplens.org/papers/pdf/explain- http://www.grouplens.org/papers/pdf/explain-CSCW.pdfCSCW.pdf

OutlineOutline

• IntroductionIntroduction

1.1. Preferences SpecificationPreferences Specification

2.2. Preferences AggregationPreferences Aggregation

3.3. Explaining RecommendationsExplaining Recommendations

4.4. Final DecisionFinal Decision

• ConclusionsConclusions

IIntroductionntroduction

ScenariosScenarios

• Group of friends going on vacation Group of friends going on vacation togethertogether

• A family selecting movie or TV A family selecting movie or TV show to watch togethershow to watch together

• A group of colleagues choosing a A group of colleagues choosing a restaurant for an evening outrestaurant for an evening out

• Keyword Keyword togethertogether

II

Issues: Phase Issues: Phase 11

• Members specify their preferenceMembers specify their preference• It may be desirable for members to It may be desirable for members to

examine each other’s preference examine each other’s preference specificationspecification

• What benefits and drawbacks can What benefits and drawbacks can such examination have and how such examination have and how can it be supported by the system?can it be supported by the system?

II

Issues: Phase Issues: Phase 22

• The system generates The system generates recommendationsrecommendations

• Some procedures for aggregating Some procedures for aggregating preferences must be appliedpreferences must be applied

• What conditions to such What conditions to such aggregation procedures have to be aggregation procedures have to be fulfilled and what kind of fulfilled and what kind of procedures tend to fulfill them?procedures tend to fulfill them?

II

Issues: Phase Issues: Phase 33

• The system presents The system presents recommendations to the membersrecommendations to the members

• The (possibly different) suitability The (possibly different) suitability of a solution for the individual of a solution for the individual members becomes an important members becomes an important aspect of solutionaspect of solution

• How can relevant information How can relevant information about suitability for individual about suitability for individual members be presented effectively?members be presented effectively?

II

Issues: Phase Issues: Phase 44

• Members decide which Members decide which recommendation (if any) to acceptrecommendation (if any) to accept

• The final decision is not necessarily The final decision is not necessarily made by a single person – made by a single person – negotiation may be requirednegotiation may be required

• How can the system support the How can the system support the process of arriving at a final process of arriving at a final decision, in particular when decision, in particular when members cannot engage in a face-members cannot engage in a face-to-face discussion?to-face discussion?

II

vsvs Collaborative Filtering Collaborative Filtering

• CF model groups of users…CF model groups of users…• ……using using similarity measuresimilarity measure, i.e. , i.e.

shared:shared:– PreferencesPreferences– Rating patternsRating patterns– etc.etc.

• GR model groups of users…GR model groups of users…• ……defined by a defined by a social contextsocial context::

– Potentially much less similaritiesPotentially much less similarities

II

SystemsSystems

• Let’s Browse Let’s Browse browsing the Web browsing the Web• PolyLens PolyLens movie recommender movie recommender• IntrigueIntrigue tour guide assistant tour guide assistant• MusicFXMusicFX automatic music automatic music

selectionselection• Travel Decision ForumTravel Decision Forum vacation vacation

plannerplanner• I-SpyI-Spy Web search engine Web search engine• Adaptive RadioAdaptive Radio music broadcast music broadcast

in a shared environmentin a shared environment

II

PPreferencesreferences SSpecificationpecification

11

MethodsMethods

• Implicit – whenever possibleImplicit – whenever possible• Explicit – sometimes unavoidableExplicit – sometimes unavoidable

• MusicFX MusicFX rating 91 genres rating 91 genres• Travel Decision Forum Travel Decision Forum rating rating

variety of attributes of vacations variety of attributes of vacations destinationsdestinations

• Adaptive Radio Adaptive Radio censoring disliked censoring disliked songssongs

• I-Spy I-Spy selecting a link selecting a link

PSPS

Sharing PreferencesSharing Preferences

1.1. Saving effortSaving effort

2.2. Learning from other membersLearning from other members

““I can’t go hiking, because of an I can’t go hiking, because of an injury”injury”

• Travel Decision Forum Travel Decision Forum copy + copy + editedit

PSPS

Travel Decision ForumTravel Decision ForumPSPS

Sharing PreferencesSharing Preferences

• Taking into account attitudes and Taking into account attitudes and anticipated behavior of other anticipated behavior of other membersmembers

• Encouraging assimilation to Encouraging assimilation to facilitate the reaching of facilitate the reaching of agreementagreement

PSPS

PPreferences references AAggregationggregation

22

Individual ModelsIndividual Models

1.1. For each candidate For each candidate cc– For each member For each member mm predict the predict the

rating rating rrcmcm– Compute an aggregate rating Compute an aggregate rating RRcc

2.2. Recommend the set of candidates Recommend the set of candidates with the highest predicted ratings with the highest predicted ratings RRcc

• RRcc = max r = max rcmcm

PAPA

Group ModelGroup Model

1.1. Compute an aggregate Compute an aggregate preference model preference model MM that that represents the preferences of the represents the preferences of the group as a whole.group as a whole.

2.2. For each candidate For each candidate cc use use MM to to predict the rating predict the rating RRcc for the group for the group as a whole.as a whole.

3.3. Recommend the set of candidates Recommend the set of candidates with the highest predicted ratings with the highest predicted ratings RRcc..

PAPA

Group Model: DetailsGroup Model: Details

• Preferences defined and Preferences defined and negotiated oncenegotiated once

• Privacy issue avoidedPrivacy issue avoided

• Recommending (accurately or not) Recommending (accurately or not) a candidate for which the a candidate for which the predicted rating of each individual predicted rating of each individual member was lowmember was low

PAPA

Goals and ProceduresGoals and Procedures

• Maximizing average satisfactionMaximizing average satisfaction• Minimizing miseryMinimizing misery• Ensuring some degree of fairnessEnsuring some degree of fairness• Discouraging manipulation of the Discouraging manipulation of the

recommendation mechanism recommendation mechanism ((……))• Ensuring some degree of Ensuring some degree of

comprehensibilitycomprehensibility• Treating different group members Treating different group members

differently (where appropriate)differently (where appropriate)

PAPA

Counteracting Counteracting ManipulationManipulation• Not showing preferences of other’s Not showing preferences of other’s

before specifying own ones:before specifying own ones:– Guessing (at least roughly)Guessing (at least roughly)– Advantages of showing themAdvantages of showing them

• Manipulation can most likely Manipulation can most likely happen…happen…

• ……with explicit preference with explicit preference specification specification as anas an inputinput

PAPA

Counteracting Counteracting ManipulationManipulationSolution…Solution…• ……explicit model with explicit model with trust factortrust factor• I-SpyI-Spy::

– Clicking on a link promotes it – easy to Clicking on a link promotes it – easy to observe and abuseobserve and abuse

– Each link selection action is evaluated Each link selection action is evaluated for reliabilityfor reliability

– No promotion unless a threshold is No promotion unless a threshold is reachedreached

PAPA

Counteracting Counteracting ManipulationManipulation• Inherently Inherently nonmanipulable nonmanipulable

mechanism?mechanism?• Automatic generation?Automatic generation?

• Travel Decision ForumTravel Decision Forum::– MedianMedian of the individual preferences of the individual preferences

used as a preference of the group as a used as a preference of the group as a wholewhole

– Automatic generation on the flyAutomatic generation on the fly

PAPA

Right Procedure – LevelsRight Procedure – Levels

1.1. By designers – before By designers – before deployment:deployment:– System’s goals/assumptions/context System’s goals/assumptions/context

drivendriven– PolyLens PolyLens small groups small groups “least “least

misery” aggregation functionmisery” aggregation function– Avoiding manipulation not always Avoiding manipulation not always

necessary:necessary:• Purchasing decisions as inputPurchasing decisions as input

PAPA

Right Procedure – LevelsRight Procedure – Levels

2.2. By users – aggregation function By users – aggregation function selection:selection:– Before any recommendations are Before any recommendations are

mademade– During an iterative process of During an iterative process of

requesting recommendationsrequesting recommendations– IntrigueIntrigue different weights for different weights for

subgroupssubgroups– Travel Decision ForumTravel Decision Forum variety of variety of

aggregation mechanismsaggregation mechanisms

PAPA

Right Procedure – LevelsRight Procedure – Levels

3.3. By users – specific By users – specific recommendation consideration:recommendation consideration:– User compiles the recommendations User compiles the recommendations

with the goal in mind before making with the goal in mind before making the final decisionthe final decision

– The system should take those goals The system should take those goals into account too to ensure that the into account too to ensure that the set of candidates includes one or set of candidates includes one or more highly suitable optionmore highly suitable option

PAPA

Multiple DecisionsMultiple Decisions

• Larger set of decisions at the same Larger set of decisions at the same time or in successiontime or in succession

• IntrigueIntrigue several sights to visit several sights to visit• Let’s BrowseLet’s Browse number of web pages number of web pages

in the course of a given sessionin the course of a given session• Local Local vs.vs. Global: Global:

– L: none of the members satisfiedL: none of the members satisfied– G: each member satisfied some of the G: each member satisfied some of the

timetime

• Decisions as a packageDecisions as a package

PAPA

EExplaining xplaining RRecommendationsecommendations

33

MotivationMotivation

• Black boxBlack box does not provide insight does not provide insight into:into:– How the recommendations were arrived How the recommendations were arrived

atat– How attractive they are for each How attractive they are for each

individual memberindividual member

• Explanations:Explanations:– Provide Provide transparencytransparency– Helps to detect sources of errorsHelps to detect sources of errors

• Important especially in high-risk Important especially in high-risk domainsdomains

ERER

Benefits for the UserBenefits for the User

• JustificationJustification – how much – how much confidence will I place in that confidence will I place in that recommendationrecommendation

• User InvolvementUser Involvement – user adds their – user adds their knowledge and inference skillsknowledge and inference skills

• EducationEducation – better understanding – better understanding the strengths and limitationsthe strengths and limitations

• AcceptanceAcceptance – as a decision support – as a decision support tooltool

ERER

Let’s BrowseLet’s BrowseERER

PolyLensPolyLensERER

GG II

IntrigueIntrigueERER

I-SpyI-Spy

• How other community members How other community members have dealt with a given pagehave dealt with a given page

• Information offered:Information offered:– Related queriesRelated queries– Quantitative and temporal Quantitative and temporal

informationinformation

ERER

Travel Decision ForumTravel Decision ForumERER

Travel Decision ForumTravel Decision Forum

• Simulated reaction effects:Simulated reaction effects:– Increased awareness of other Increased awareness of other

members’ point of viewmembers’ point of view– Overcoming the natural tendency to Overcoming the natural tendency to

focus on one’s own evaluationsfocus on one’s own evaluations

ERER

FFinalinal D Decisionecision

44

ConsiderationsConsiderations

• The decision is not made by a The decision is not made by a single person and therefore…single person and therefore…

• ……extensive debate and extensive debate and negotiations may be requirednegotiations may be required

• Can members communicate easily?Can members communicate easily?

FDFD

Existing Approach Existing Approach 11

1.1. AutonomousAutonomous translation of most translation of most highly rated solutions into actionshighly rated solutions into actions

• MusicFXMusicFX changes the channel changes the channel• Adaptive RadioAdaptive Radio changes the changes the

songsong

• Good when a quick decision is Good when a quick decision is neededneeded

FDFD

Existing Approach Existing Approach 22

2.2. OneOne group membergroup member is responsible is responsible for making the final decisionfor making the final decision

• Let’s BrowseLet’s Browse one person is one person is controlling the pointing devicecontrolling the pointing device

• IntrigueIntrigue tourist guide is tourist guide is deciding what tour should be deciding what tour should be takentaken

• Makes the system design simplerMakes the system design simpler

FDFD

Existing Approach Existing Approach 33

3.3. Conventional conversationConventional conversation (face- (face-to-face or by phone) as a mediumto-face or by phone) as a medium

• PolyLensPolyLens members can call/IM members can call/IM each othereach other

• Makes the system design simplerMakes the system design simpler

FDFD

Existing Approach Existing Approach 44

4.4. Built-inBuilt-in communication support communication support

• Travel Decision Forum Travel Decision Forum avatars avatars can be granted a certain amount can be granted a certain amount of authority to accept proposals of authority to accept proposals during interactions with other during interactions with other membersmembers

• Makes the system design difficultMakes the system design difficult

FDFD

Possible ExtensionsPossible Extensions

• Thresholds of acceptanceThresholds of acceptance• VotingVoting• Isn’t voting itself recommending?Isn’t voting itself recommending?

– Seeing or not seeing votes of othersSeeing or not seeing votes of others– Counting and weighting votesCounting and weighting votes– Presenting the results of votingPresenting the results of voting– How to arrive at the final decisionHow to arrive at the final decision

• Yes, but in a much simpler Yes, but in a much simpler context…context…

• ……which means it is better definedwhich means it is better defined

FDFD

Conclusions!Conclusions!

The The 44 Phases Phases

1.1. Preferences SpecificationPreferences Specification

2.2. Preferences AggregationPreferences Aggregation

3.3. Explaining RecommendationsExplaining Recommendations

4.4. Final DecisionFinal Decision

CC

Group RecommendersGroup Recommenders

• Only few systemsOnly few systems• Small subset of possible Small subset of possible

recommendation techniquesrecommendation techniques• Limited number of application Limited number of application

domainsdomains• Different superficially onlyDifferent superficially only• Context dependantContext dependant

CC

Other SystemsOther Systems

• What happens if…What happens if…• ……we have groups of cooperating, we have groups of cooperating,

information seeking user?information seeking user?• We can see how would the We can see how would the 4 4

phasesphases be applied be applied• For instance, adaptive navigation For instance, adaptive navigation

supportsupport

CC

I-Spy Demo?I-Spy Demo?CC

Thank you!Thank you!