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Ontology-Based User Modeling for Pedestrian Navigation Systems

This paper discusses the importance of personalized navigation systems for pedestrians, emphasizing the need for ontology-based user modeling. It outlines the wayfinding process and the factors influencing navigation, such as individual characteristics and environmental features. The study presents OntoNav, a semantic navigation system that leverages user profiles defined through an ontology to optimize indoor navigation experience. It aims to address diverse user needs, ensuring accessibility for all. Future research directions emphasize user profile inference and practical evaluations.

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Ontology-Based User Modeling for Pedestrian Navigation Systems

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  1. Ontology-Based User Modeling for Pedestrian Navigation Systems Panayotis Kikiras, Vassileios Tsetsos, and Stathes Hadjiefthymiades Pervasive Computing Research Group Communication Networks Laboratory Department of Informatics and Telecommunications University of Athens – Greece UbiqUM ’06 @ Riva del Garda

  2. Outline • Pedestrian Wayfinding and Navigation: The Theory • Ontology-based User Modeling • Existing User Models • User Navigation Ontology • OntoNav: A Semantic Navigation System • Conclusion & Future Research

  3. What Is Wayfinding • A cognitive procedure for orientation and navigation of the user in huge and complex environments • Involves four main steps: • Orientation • Route Selection • Routing Control • Recognition of destination

  4. What Affects Wayfinding • Individual’s characteristics • Sex, age, perceptual and mental abilities, motor abilities, prior knowledge of the environment, … • Environment’s characteristics • Luminosity, signage, structure, obstacles, … • Learning processes • Learning abilities & strategies, … Not everyone has the same navigational skills  Personalized navigation is necessary

  5. User Profile Components Orientation disability Mental impairment Wheelchair Escort-aided mobility Hearing abilities Visual quality Mental/Cognitive Characteristics Sensory Abilities Motor Abilities User Profile Navigational Preferences User Interface Preferences User Demographics Avoid stairs Only audio info Only visual info Age Gender

  6. Ontology-based User Modeling • Ontology is • “a formal, explicit specification of a shared conceptualization” (Studer, 1998 - original: Gruber, 1993) • a core knowledge representation technique in Semantic Web (OWL language) • User types ↔ ontology classes • User characteristics ↔ class properties • Such modeling enables Semantic Web reasoning (e.g., classification) and inference (i.e., rules)

  7. Existing User Models • GUMO (General User Model Ontology) • Represents user dimensions (e.g., demographics, abilities) + Developed in OWL - Provides just a vocabulary (no axioms, restrictions) • UserML • XML language • Provides just a syntax layer for higher level semantic models

  8. User Navigation Ontology (UNO) • An OWL ontology that specifies classes and properties for the components of a navigation user profile • User classes are formally defined YoungWheelchairedUser ≡ ∃ hasAbility AutonomousWheelchairedMobility ∃ hasAge LessThan18 • Enables dynamic classification of users through Description Logics reasoning • UNO is aligned with GUMO (where applicable)

  9. UNO Elements Classes Properties

  10. OntoNav • Personalized indoor navigation, through the exploitation of user- and building-related semantics User Profile Creator UNO Building graph User-compatible graph Path Computation and Ranking Rules Building Blueprints IF UNO:WheelchairedUser(u) AND INO:Stairway(s) THEN INO:isExcludedFor(s,u) INO

  11. User Profile Creation • Users can A) Choose from predefined profiles B) Create a custom profile through forms • Both options demonstrate serious limitations • A is too coarse-grained • B is not automated and requires (substantial) user effort • Users may be reluctant to disclose (all of) their abilities/disabilities (A&B) Solution (+challenge): User Profile Inference and Calibration from user movement, history, published personal information (e.g., homepage), …

  12. Conclusion • A first attempt to define an “axiomatized” ontology for describing pedestrian users based on theories and existing work • Integration of UNO with a navigation system (i.e., Location Based Services) • Future Research Issues • User profile inference • Evaluation with real users • National project on Universal Access to Indoor LBS (GSRT MNISIKLIS)

  13. Thank You! Questions??? UNO v0.1 available at: http://p-comp.di.uoa.gr/ont/UNO.owl

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