PERSONALIZING HUMAN INTERACTION THROUGH HYBRID ONTOLOGICAL PROFILING: CULTURAL HERITAGE CASE STUDYNima Dokoohaki, Mihhail MatskinBangkok, Thailand, February 2nd 2009

First workshop on Semantic Web Applications and Human Aspects (SWAHA)

Royal Institute of technology (KTH),Stockholm, Sweden

Content

Motivation Problem Description/Formulation Contribution

User Profile Profile Structure

Records (segments) Semantic network of user profile

Extending CH ontologies with User keywords User Model ontology CH Metadata + Human User Metadata

Conclusion/Future Work Questions

General Problem

Scenario: Constructing a Semantics-aided Museum

(Cultural Heritage) knowledge Platform Clients are mobile devices which guide users

through exhibit Goals:

Improving structured, user behaviour and preference dependent access to cultural heritage repositories Approach taken: User modelling and profiling

Bringing personalised cultural experience closer to non-expert communities Approach taken: Personalization techniques;

Collaborative Filtering Recommender Systems

Contribution

Need for a hybrid approach Allows description of the user attributes Recording history of user access for

personalized, adaptive and interactive experience

Need for a generic structure Structure that allows incorporation of all kinds

of usage attributes [Domain independence] Weight(s) can be assigned to recorded

materials [Weighted profiles] Structure that can be presented in

[Interoperable] high level formats (OWL/RDF) low level formats (XML/Database)

Profile Structure

A Generic Structure Used for saving and retrieving different types

of information that document both behavior and knowledge aspects of the user.

Documents Personal information about the user History and evidence of the Usage

experience Weight of the information recorded

Structural descriptions Depth (hierarchy) Length (flat structure)

Profile RecordsProfile Records

Example: Records of visit of user to museum:

< Reference to Context, visited, “artifact name”, atTime{Date time/date value}, Rank, Privacy, Trust>

<http://smartmuseum.eu/ns/context/weather#, visited, Venere, atDate 20081210 , 0.8, 0.5, 0.6>

Example: Records of visit of user to museum:

< Reference to Context, visited, “artifact name”, atTime{Date time/date value}, Rank, Privacy, Trust>

<http://smartmuseum.eu/ns/context/weather#, visited, Venere, atDate 20081210 , 0.8, 0.5, 0.6>

User ProfileUser Profile

Italian Renaissance

Sandro Botticelli

Michelangelo Buonarroti

Primavera

David

Venere

Holy Family

Early Renaissance

Late Renaissance

Semantic Profile NetworkSemantic Profile Network

hasPainted

hasArtist

hasArtist

hasCreated hasPaintedhasPainted

Semantic Profile NetworkSemantic Profile Network

Visualized by RDF Gravity, http://semweb.salzburgresearch.at/apps/rdf-gravity/download.html

Improving personalization through cultural heritage extension with user model We can extend existing [legacy] cultural

heritage keyword-set to contain Human attributes [extended] Construct a user model ontology to describe

attributes of our user The user model ontology concepts are used to

expand legacy concepts for cultural heritage Aim: Improving recommendations

(information retrieved on user’s behalf) Through query expansion

Expanded query contains user attributes (profiles) Efficient individual/group matchmaking

Similar instances are on both sides item instances and user profiles

Extending Metadata with Human Attributes (User Model Ontology)

Perspectives

Categories

Schema

Instances

All

SUM:Age Group

SUM:Knowledge

Group

TGN:Place

ULAN:Person AAT:

Concept

VRA:Work

VRA:techniqueVRA:Material

VRA:CreatorVRA:location.CreationSite

SM: SuitesAgeGroup

SM:SuitesKnowledgeGroup

SUM:Tour.

TourName

SM: IncludedinTour

SUM:Visitor

Typology

SM: SuitesVisitorType

SM:Companion SUM:visit.

Companion

Greedy

Virtual Uffizi

Florence

Adult

Sandro Botticelli

Venere

Tempera on Canvas

Teenager

Selective

Parent

IncludedinTour

SuitesVisitorType

SuitesVisitorType

CreationSiteCreator

Material

SuitesKnowledgeGroup

Companion

SuitesAgeGroupSuitesAgeGroup

Extended CH keywords with Human

Extended CH keywords with Human

Conclusion / Future work

Conclusions User Behavior models ( Profiling / Modeling) seem to become

dominant approaches in addressing problems of altering structure of human-system

interactions, specifying and presenting of preferences of human users

Personalization techniques seem to become dominant approaches in

information dissemination Future work

Focused study of personalization effect based on profile/model Implementing personalization services based on user

profile/model Recommendation [ongoing]

Improving existing recommendation based on weight values [ongoing]

Questions ?

Thank you !

Nima Dokoohaki

School of Information and Communications Technology (ICT ),

Royal Institute of Technology ( KTH ),Stockholm,Sweden

Office: +46 (0) 8 790 4149Cell : +46 (0) 76 269 76 30Fax: +46 (0) 8 751 1793

nimad@kth.se

http://web.it.kth.se/~nimad/