Personalization in EPOS, SWP06, Budva Personalization in the EPOS project Leo Sauermann, Andreas Dengel, Ludger van Elst, Andreas Lauer, Heiko Maus, Sven Schwarz DFKI GmbH persona created using

Personalization in EPOS, SWP06, Budva Leo Sauermann

Personalization in EPOS, SWP06, Budva : no personalization without the person

Personalization in EPOS, SWP06, Budva : no person without the subjective data of the person (from the computer’s perspective)

Personalization in EPOS, SWP06, Budva Rom e Peter Paul’s mental model Paul’s concepts pimo-things Paul’s files and digital resources paul:Rome relations to occurrences

Personalization in EPOS, SWP06, Budva Results of the EPOS project Paul what do I do with this ? where is Peter? Semantic Web Applications, data, web, trust, ontologies, …

Personalization in EPOS, SWP06, Budva Szenario of EPOS Knowledge Worker „Paul“ using Desktop PC Problem: Data about single ideas are stored in several applications and without context Files ↔ s Semantic Desktop Paul

Personalization in EPOS, SWP06, Budva dc:language = AEHS Adaptive Educational Hypermedia System AEHS Document Space DOCS User Model UM Observations OBS Adaptation Component AC

Personalization in EPOS, SWP06, Budva Three contributions A representation of the user’s personal information items, including s, 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

Personalization in EPOS, SWP06, Budva PIMO = Personal Information Model

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva PIMO is filled automatically from data Data Paul‘s files & s RDF Database adapter to RDF matching to ontology PIMO Store aperture.sf.net (check it out!)

Personalization in EPOS, SWP06, Budva PIMO used and extended

Personalization in EPOS, SWP06, Budva domain-independent SemDesk Upper Level PersonRoleDocumentOrganizationTime domain-independent, adapted to Semantic Desktop and Nepomuk SemDesk Mid-Level ManagerProject Contract CompanyOffer basic superclasses Rep Lang SystemItemsThing ontology imports Message dfki.de/ont/pim/pimo PIMO ontology languages PIMO-Basic defines the basic language constructs. PIMO-Upper A 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.

Personalization in EPOS, SWP06, Budva Organizational Structure Domain Model: Bibtech A HeikoCar-EntReport56 Report EPOS dfki.de/ont/pim/pimo 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.

Personalization in EPOS, SWP06, Budva basic superclasses Rep Lang SystemItems domain-independent SemDesk Upper Level PersonRoleDocumentOrganizationTime domain-independent, adapted to Semantic Desktop and Nepomuk SemDesk Mid-Level ManagerProject Contract CompanyOffer representing extracted data in RDF/S multiple vocabularies Native Data Vocabularies vCard vEventdublin core foaf image PersonImage Thing sub-classes Organizational Structure Domain Model: Bibtech A HeikoCar-EntReport56 Report EPOS ontology imports Message aperture.semanticdesktop.org/data dfki.de/ont/pim/pimo all PIMO ontology layers

Personalization in EPOS, SWP06, Budva 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 Z Report41 File X 2 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

Personalization in EPOS, SWP06, Budva 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/ s attached to the categories –OBS the current context of the user This holistic user model can now be used for several personalized applications

Personalization in EPOS, SWP06, Budva Paul Context Service Plugins gather user actions Elicitation of task concepts Notification of GUI Bayesian Network UA Domain Wf Task NOP Wf Task TaCo Domain UA NOP PIM Maus PIM Mid DFKI KM PIM Upper PIM Basic

Personalization in EPOS, SWP06, Budva 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.

Personalization in EPOS, SWP06, Budva Applications

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva 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:Epos EPOS, DFKI, Maus, … PIMO of Paul =

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva Semantic Search

Personalization in EPOS, SWP06, Budva Evaluation

Personalization in EPOS, SWP06, Budva 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”

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva 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 ….

Personalization in EPOS, SWP06, Budva Semantic Search evaluated at Siemens SBS by Mark Siebert and Pierre Smits customization features used integrated a proposal ontology conclusion: Through peer search and semantic enhancements, recall was increased. Precision may decrease, depending on the setup and scenario.

Personalization in EPOS, SWP06, Budva Outlook

Personalization in EPOS, SWP06, Budva Our goal This is my personal computer

Personalization in EPOS, SWP06, Budva Semantic Applications Desktop Search Gnowsis Server Aperture Crawlers Outlook server filesystem Outlook PIMO Editor Crawler Ont. Matching Files 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

Personalization in EPOS, SWP06, Budva EPOS will be continued our results are code for you Open source and reusable gnowsis-beta Nepomuk MyMory

Personalization in EPOS, SWP06, Budva note: Demo of Nepomuk today at the EU projects session I can demo gnowsis beta 0.9

Personalization in EPOS, SWP06, Budva 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

Personalization in EPOS, SWP06, Budva Questions persona created using