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The PROMPT Suite . Interactive Tools For Ontology Merging And Mapping. 1. Managing Multiple Ontologies. Many different parties develop ontologies Overlapping content: For example Yahoo! and Dmoz.org) What if we wanted to use them both as they were just one ontology? Merging
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The PROMPT Suite Interactive Tools For Ontology Merging And Mapping
1. Managing Multiple Ontologies • Many different parties develop ontologies • Overlapping content: For example Yahoo! and Dmoz.org) • What if we wanted to use them both as they were just one ontology? • Merging • Aligning / Mapping • We would have to: • Find the similarities • Determine what the similarities are • … and decide what to do next.
2. The PROMPT Knownledge Model • PROMPT: Extension to the Proégé ontology-editing enviroment • Frame-based • Principal building blocks • Each frame has a unique name • Three types of frame types • Classes • Slots • Instances
Frames: Class, instances and slots • Class: A set of entities • Hierarchy multiple inheritance • Instances: Elements of class’ set. • The class of an instance is called its type • Each instance can have only one type • Slots: ”The glue” between classes – The data of an instance • Attached to classes (it’s domain). • Defines binary relations between instances • Attributes of the instances • Can have a range defined • Another class (in which case a slot is a binary relation) • Primitive datatype (String, Integer, Float, and Boolean) • Cardinality: The number of values a slot can have (min, max) • A slot attached to a class is also attached to its subclasses
3. The PROMPT Framework • A single framework for working width muliple ontologies • Includes the tools: • IPrompt (Merging tool) • AnchorPrompt (Alignment tool) • PromptDiff (Versioning tool) • PromptFactor (Find semantically complete sub-ontologies)
4. IPROMPT • An interactive ontology-merging tool • Takes two ontologies as input • Guides the user in the creation of one merged ontology as output … but how?
IPROMPT – INN MED FIGUR 3 • Creates an initial list of matches based on lexical similarity of class names. • Then, the following cycle is done: • The user acepts IPROMPTs suggestion OR uses the ontology-editing methods directly • IPROMPT performs the operation, generates a list of suggestions for the user and determines inconsistencies and potential problems and finds possible solutions for those problems.
4.1.1 The IPROMPT Operations • Merge classes • Class A and B becomes M in Om • Any subclasses of A or B become subclasses of M. • All slot-references to A or B are attached to M. • A and B is deleted.
Merge slots • S1 and S2 becomes Sm • For each class C in the domain or range of S1 and S2, add Ci to the domain or range of Sm • Merge instances • I1 and I2 becomes Im • If the the types (their classes) is missing in Om; copy them into Om by using the operationperform a shallow copy of a class • Perform a shallow copy of a class • Copy class C to Ci to Om • For each slot S directly attached to C, if its not already in Om, copy it into Om as well and attach it to Ci.
Perform a deep copy of a class • First do a shallow copy of C to Om, then: • Copy all its parents classes up to the root of the hierarchy to Om.
4.1.2 Inconsistencies and potential problems • Name conflicts • Solution: Rename • Dangling references • Possible solution: Copy missing frames into the Ontology • Redundancy in the class hierarchy • Possible solution: Remove one parent • Slot values violating slot-value restrictions
4.2 The IPROMPT Tool • Additional features of the IPROMPT tool • Setting the preferred ontology • Lets the system resolve conflicts automatically. • Maintaining the user’s focus • One part of the ontology at a time • Providing feedback to the user • Why did IPROMPT suggest… • Logging and reapplying the operations • Reapply operations (almost) automatically.
AnchorPrompt • Goal • Help IPROMPT find similarity between ontologies. Same term names not needed. • Assumption • Developers link the terms in the ontology in a similar manner. • Input • Set of pairs of related terms. • Output • Ranked set of new pairs of semantically close terms.
AnchorPrompt • Views each otology O as a directed labelled graph G. • Each class C is a node • Each slot S is a edge • If, starting at node A, it is possible to follow a sequence of adjaced edges to reach node B, there is at path between A and B. • Lenght of the path is the number of edges
Merging Is one ontologi more desirable than the other? Should all the infomation in both ontoligies be used? Aligning The main choices…