personalization in the epos project

Personalization in EPOS, SWP06, Budva 12.06.2006

Personalization in the EPOS project

Leo Sauermann, Andreas Dengel, Ludger van Elst, Andreas Lauer, Heiko Maus, Sven Schwarz

DFKI GmbH

12.06.2006

persona created using http://www.sp-studio.de/


Leo Sauermann


1: no personalization without the person


2: no person without the subjective data of the

person(from the computer’s

perspective)


• Results of the EPOS project

Paul

what do I do with this e-mail?where is Peter?

Semantic Web

Applications, data, web, trust,ontologies, …


Szenario of EPOS

• Knowledge Worker „Paul“ using Desktop PC• Problem: Data about single ideas are stored in

several applications and without context

Files ↔ Emails

Semantic Desktop

Paul


dc:language = AEHS

• Adaptive Educational Hypermedia System AEHS

• Document Space DOCS

• User Model UM

• Observations OBS

• Adaptation Component AC


Three contributions• A representation of the user’s personal information

items, including e-mails, files, and other data sources using RDF„native resources“ = DOCS

• A representation of the user’s mental model in a formal representation, using several layered ontologies.„PIMO“

• A desktop service to capture the current actions of the user, representing the actions using RDF and then calculating the current context of the user.„Context Server“ = OBS

• UM = DOCS + PIMO + OBS• Adaptive Applications


PIMO = Personal Information Model


From native structures to PIMO

• Native data is expressed in RDF– DOCS– RDF/S vocabularies like foaf,

vCard, Dublin Core– data + structures

• Personal Information Model PIMO– Personal Concepts

• Topics• Places• People• Types• Workflow

• with relations to files and folders


PIMO is The “personal ontology”

• “shared” across applications

• filled from DOCS, Company ontologies and domain ontologies

• used by the – user– creates instances– creates classes & properties (on the fly)– annotates


PIMO is filled

• automatically from data

DataPaul‘s files & e-mails

RDF Database

adapter to RDF

matchingto

ontology

PIMO Store

aperture.sf.net(check it out!)


PIMO used and extended


domain-independentdomain-independent

SemDesk Upper Level

Person Role Document OrganizationTime

domain-independent, adapted to Semantic Desktop and Nepomuk


SemDesk Mid-Level

Manager Project

Contract

CompanyOffer

basic superclassesbasic superclasses

Rep Lang

SystemItemsThing

ont

olo

gy

imp

ort

sMessage

dfki.de/ont/pim/pimo

PIMO ontology languages• PIMO-Basic

defines the basic language constructs.

• PIMO-UpperA domain-independent ontology defining abstract sub-classes of Thing.

• PIMO-Mid: More concrete sub-classes of upper-classes. The EPOS mid-level ontology serves to integrate various domain ontologies and provides classes for Person, Project, Company, etc.


Organizational StructureOrganizational Structure

Domain Model: Bibtech A

Heiko Car-Ent Report56

Report

EPOS


PIMO ontology languages• Domain ontologies

A set of domain ontologies where each describes a concrete domain of interest of the user. The user’s company and its organizational structure may be such a domain, or a shared public ontology.


basic superclassesbasic superclasses

Rep Lang

SystemItems

domain-independentdomain-independent

SemDesk Upper Level

Person Role Document OrganizationTime



SemDesk Mid-Level

Manager Project

Contract

CompanyOffer

representing extracted data in RDF/Smultiple vocabularies

representing extracted data in RDF/Smultiple vocabularies

Native Data Vocabularies

vCard

vEvent dublin core

foafimage

Person Image

Thing

sub-classes

Organizational StructureOrganizational Structure

Domain Model: Bibtech A

Heiko Car-Ent Report56

Report

EPOS

ont

olo

gy

imp

ort

sMessage

aperture.semanticdesktop.org/data


all PIMO ontology layers


Paul

Paul‘s PIMO - Personal Information Model

personal information model of one user Imports all other ontologies and defines extensions

Ontology side Native Resources

personal information model of one user Imports all other ontologies and defines extensions

Ontology side Native Resources

PIMO of Person:Paul

Paul

Project ZReport41

File X e-mail2

vCard H

Rep Lang

SemDesk Upper Level

SemDesk Mid-Level

Native Data Vocabularies

Domain: Bibtech A

Domain: Paul’s company

Paul imports all of them


User Model

• UM = DOCS + PIMO + OBS

• To capture a user model, we need to know – PIMO the categories/model of the user– DOCS the documents/e-mails attached to the

categories– OBS the current context of the user

• This holistic user model can now be used for several personalized applications


Paul

Context Service

• Plugins gather user actions

• Elicitation of task concepts

• Notification of GUI

Bayesian Network

UA UA

Domain

Wf Task

NOP NOP NOP NOP

Wf Task

TaCo

Domain

UA

NOP

PIMMaus

PIM MidDFKI KM

PIM Upper

PIM Basic


Context Representation

• Context in EPOS– context of a knowledge worker– context shall support (personal) knowledge management

• Contextual elements (CEs)– relevant documents, topics, places, actions, tasks,

organizational entities, …– from the user's DOCS and PIMO– not alien data, but known, familiar entities and structures

• Service Oriented Architecture– ContextService– gathers events using RDF messages from Plugins– represents context as RDF model, using the PIMO

S. Schwarz. A context model for personal knowledge management. In Proceedings of the IJCAII WS. on Modeling and Retrieval of Context, Edinburgh, 2005.


Applications


Context Assistance

• Sidebar• can be switched off• shows current context

– documents– people– projects– topics

• changes dynamically• use: open related information, pro-active,

non-obtrusive assistance system


Application: Drop Box• Helps filing information• uses PIMO structures

concepts and folders• uses DOCS for text similarity• Knows the users model and is

trained by using it• process flow

– files are stored into a Drop-Box folder– files are text-analysed and possible

target folders are suggested– Drop-Box user interface shows– user selects a folder, classify– files are moved and classified

• not used, but obvious:OBS – current context

doc:… EPOS …

Project:EposEPOS, DFKI,Maus, …

PIMO of Paul

=


Semantic Search• search over EPOS data (PIMO)• can be personalized using rules SPARQL queries• example

# found something? -> infer other representations via SPARQL

(?hit retrieve:item ?x) -> querySparql('CONSTRUCT { ?x

pimbasic:hasOtherRepresentation ?y } ')

# found a project? -> also show members(?hit retrieve:item ?project),(?project rdf:type org:Project) ->querySparql('CONSTRUCT { ?project org:containsMember ?m.}).

• Innovation– search result expansion using SPARQL– customized rules for search – only when word “x” is searched, include

these results, etc


Semantic Search


Evaluation


Methodology used for Evaluation in EPOS• Case Study Method

– Case Study with 8 researchers from DFKI– Preperation Phase three months: users learn the system, bugfixing– Evaluation period of 1 week with daily usage– Daily interviews with questionnaire– Usage data collection– Explicit user feedback for proposals from context elicitation – user

had to check if results were correct

• General observations from questionnaire– Personal Ontology represents the view of the user (90% positive

answers) – it is “valuable” for searching and classifying information– Semantic Desktop is perceived as “helpful in their daily work”


Example findings from Case Study• Move & Classify via EPOS DropBox

– Filing is faster than before due to proposal of locations?

• Yes on 40% of all days• There was still manual filing, but only in 8% of all reported

filings

– Multiple classification have been used 2,5 categories per file: multicriterial classification• PIMO is populated on-the-fly


Lessons learned: changing the linker• Before:

• Evaluation• Manual linking with the Linker was

seldom used– Whereas semi-automatic linking was

appreciated by means of Move & Classify, Topic-linking, PIM mapping

• Redesign

• After:

• Resources can be “Tagged”, the metaphor is known from Web 2.0 applications. Tags are searched semi-automatically

• Benefit is immediately seen• User interface is simpler

• … to be evaluated again ….


Outlook


Our goal

This is my personal computer


Semantic Applications

Desktop Search

GnowsisServer Aperture

Crawlers OutlookOutlook

e-mail server

e-mail server

filesystemfilesystem

OutlookOutlook

PIMO Editor

Crawler

Ont. Matching

FilesFiles

e-maile-mail

Gui invocationTagging

Clustering

Desktop ApplicationsApplication Plugins

Sesame2 Repository

Resource Store

PIMO Store

Configuration Store

Service Store

Domain Ontologies

Lucene Index

Personal Wiki

Web 2.0 Interfaces


• EPOS will be continued

• our results are code for you

Open source and reusable

• gnowsis-betahttp://www.gnowsis.org

• Nepomukhttp://nepomuk.semanticdesktop.org

• MyMoryhttp://www.dfki.de/mymory


note:

• Demo of Nepomuk today at the EU projects session

• I can demo gnowsis beta 0.9


Summary

• The PIMO ontology stack and Paul’s PIMO allow us to personalize using precise knowledge about the user

• User observation components identify contexts based on PIMO

• Applications use PIMO + context in combination

• open source, will be continued


Questions

persona created using http://www.sp-studio.de/

personalization in the epos project

Documents

epos projectpersonalization

epos projectleo sauermann

epos midlevel ontology

domainindependent ontology

various domain ontologies

company ontologies

datadatapauls files

set of domain ontologies