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Protégé An Environment for Knowledge- Based Systems Development Haishan Liu
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Outline Things will be covered The evolution of Prot é g é and the underlying driven idea Major features of different versions of Prot é g é Things will not be covered The detailed mechanisms and algorithms of the implementation
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What is Protégé The Prot é g é system is an environment for knowledge-based systems development From a single tool to reduce the knowledge-acquisition bottleneck to a general-purpose environment for knowledge modeling
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The classical model of expert system development
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Difficulties in the classic model The knowledge engineer is involved in all phases of system construction characterize the reasoning tasks identify the major domain concepts categorize the type of knowledge identify the reasoning strategies used by experts, define an inference structure for the resulting application, and formalize all this knowledge in a generic and reusable way. domain experts are seen simply as resources for knowledge engineers to draw upon.
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An early view: expert system shell Reuse of knowledge Base Knowledge acquisition is carried out by the knowledge engineer. The introduction of a knowledge engineer in between could lead to errors and misunderstandings. Time-consuming
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Domain expert
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Protégé Ancestry: Oncocin and Opal
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Information-partitioning hypothesis structural domain concepts ① domain knowledge ② case data ③ ① ② ③
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Advantage of Opal/Oncocin architecture Actual tools developed for knowledge acquisition The domain experts directly build the knowledge base reduce the likelihood of errors Streamline knowledge base construction
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Protégé-I generalization of the Oncocin/Opal architecture
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Assumptions of Protégé-I Problem specific KB Only works well on certain PSMs Problem-solving method (PSM) provides semantics of KB No formalization of the knowledge model Atomic PSM and KB Self-contained KB (no reference to the others) Single monolithic PSM
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Summary of Protégé-I Generating knowledge-acquisition tools from structured meta-knowledge Neither reusable nor general purpose Problem-specific KB Lacking formal semantics
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Protégé-II reusable problem-solving methods. A problem-solving method could be developed independently from the knowledge base. PSMs were generic algorithms that could be used with different knowledge bases to solve different real-world tasks. constraint satisfaction Classification Planning Bayesian inference
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Problem-solving knowledge automates specific tasks Domain knowledge + Problem-solving method Intelligent behavior
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Protégé-II Reusable problem-solving methods
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Developing Knowledge-based Systems with Protégé-II Developing or reusing a problem-solving method Defining an appropriate domain ontology Generating a knowledge-acquisition tool Building a knowledge base using the tool Integrating these components into a knowledge-based system defining mappings between problem-solving methods and specific knowledge bases.
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Three classes of ontologies Domain ontologies (reusable) define the concepts related to an application domain (e.g., different symptoms, anomalies, and remedies) Method ontologies (reusable) specify the data requirements of the problem- solving methods (i.e., the input and output structure of each method) Application ontologies (application specific) define the concepts that are specific to a particular application or implementation.
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Protégé-II components for building knowledge bases. “Downhill Flow” Model Knowledge engineer Domain Expert
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Integrating the Components of a Knowledge-Based System—Mappings KB and PSM are developed separately PSM may not match KB Use mapping relations to connect KB and PSM Marble – a special KA tool to build mapping relations A generic mapping interpreter producing adapted view of KB to PSM
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Summary of Protégé-II Reusable PSMs as components Adoption of ontology Generation of KA-tools from any ontology “ Downhill Flow ” assumption of class over instance
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Protégé/Win Besides the re-implementation The use of modular ontologies, via an ontology inclusion mechanism build large knowledge bases by “ gluing ” together a set of smaller, modular ontologies scale to large problems better than monolithic ontologies A more integrated, streamlined set of tools A more custom-tailoring knowledge- acquisition tool
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Protégé-2000 significant augmentations Underlying knowledge model A single unified application A plug-in architecture
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The Protégé-2000 Knowledge Model Protégé-Ihand-coded Lisp object Protégé-II and Protégé/Win a simple frame-based model provided by CLIPS Protégé-2000OKBC protocol Retrospect
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Open Knowledge Base Connectivity (OKBC) Standard mechanism to access knowledge bases stored as “ frames ” of classes and attributes Adopted by several well-known knowledge- representation systems (Ontolingua, LOOM) Will allow Prot é g é -2000 to be used as an ontology- and knowledge-editing system for any OKBC-compliant server
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OKBC – cont’d OKBC specifies a knowledge model of KRSs with KBs, classes, individuals, slots, and facets It also specifies a set of operations based on this model find a frame matching a name enumerate the slots of a frame delete a frame An application uses these operations to access and modify knowledge stored in a OKBC-compliant KRS.
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The OKBC Knowledge Model Constants Frames Slots Facets Classes Individuals knowledge bases
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Frames, slots and facets Frame primitive object that represents an entity in the domain of discourse Class Frame, Individual Frame Slot Binary relation associate to a frame (describing the property of the frame) Facet Constraints on the slot
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The plug-in architecture of Protégé-2000
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The OntoViz tab plug-in
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A Protégé-2000 KA tool for entering rules for monitoring nuclear power plants
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Elements of Protégé-2000 Slots as first-class objects Slots as first-class objects Classes and class hierarchy Classes and class hierarchy Facets standard and user-defined Facets standard and user-defined Instances Customizable instance forms Customizable instance forms Easy browsing Easy browsing Means to view large data sets Means to view large data sets Custom widgets Custom widgets Domain- specific tabs Domain- specific tabs Components for building knowledge-based applications Components for building knowledge-based applications
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