Date post: | 11-May-2015 |
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Education |
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Knowledge Representation and Semantic Web
Technologies for extended minds
Knowledge Representation Aspects
• How do we represent what we know?– Expressiveness can conflict with computability
• What aspects of what we know and their relationships are important?– Every KR is an explicit answer to this question– Every KR is a fragmented of full reasoning
• The subset useful to the problem at hand in tractable limits
– The choice of KR limits• What can be captured/expressed• What sorts of questions may be tractably answered• Usefulness for human exploration and learning• Usefulness for computational exploration and learning
KR Desired Properties
• Coverage– Sufficient breath and depth
• Understandable by humans– If for human use anyway. Useful for debugging in any case
• Consistency• Efficient• Easy of modification• Supports the applications / functions the KR was
desired for
Historical Attempts
• 70s and early 80s• Heuristic question-answering, neural networks, theorem
proving, expert systems. (Mycin)• Cyc starting is late 80s.
– Naïve physics, time notions, causality, motivation, common objects and classes of objects
• 90s to now• Computational linquistics• KR Programming languages• SGML -> HTML -> XML• Semantic Web
Uniting Information Sources
Semantic Web
• KR of web content– Machine readable web content or description of content– Integration across different content, applications,
systems• Enterprise Information Systems
– Semantic publishing• Documents with semantic markup
– RDF is most used currently
– Two Approaches• Information as data objects using semantic language (RDF,
OWL)• Embed formal metadata within documents with new markup
– RDFa, Microformats
Some ontologies and vocabularies• Dublin Core
– Resources, materials, media, text, web pages• SKOS
– Thesauri, taxonomies, classification schemes• FOAF
– Friend of a friend. Social network ontology• SIOC
– Interconnection of discussions, blogs, forums, mailing lists• RSS
– Syndication. Updates of blogs, news headlines, audio, video• DOAP
– Description of a project. 43000 OS projects in Freshmeat• SPE
– Scientific publishing experiment
Open Source Tools and Services• Ambra Project
– Publish open access journal with RDF. • Semantic MediaWiki
– Mediawiki extension for semantic annotation and RDF publishing• Swoogle
– Search engine for ontologies and instance data a• Ufeed
– Publishes RDF resources and feeds• D2R Server
– Publishes relational database on the web als Linked Data and SPARQL endpoints• BigBlogZoo
– Crawls and reaggregates 60000 XML sources under semantic URLs• Utopia
– Interactive documents
Resource Description Framework• RDF basics
– Subject predicate object• Typically all three are URIs to keep identity clear• Graphed as subject node, object node, predicate as labeled directed edge
– Basically a lightweight binary relationship– Note similarity to Prolog entries
– Structured information broken in two set of RDF triplets– Nodes, at least objects, can be containers of URIs
• Containers are unbound bags• Collections are closed / complete
• RDF Schema (RDFS)– Defines types and classes of URIs and expected associations or information
about types.• IS-A and HAS-A relationships• Meaning details for types• Properties of classes
Web Ontology Language (OWL)
• Components• Classes• Instances• Properties• Datatype properties• Object properties• operators
Topic Maps• Components
– Topics– Associations– Occurrences
• Similar to concept maps and mind maps• Higher level of semantic abstraction than OWL and RDFS• Fully supports merging of topic maps• APIs
– TMAPI • Query
– TMQL• Constraint specification (unfinished)
– TMCL