• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Change Paths In Reasoning !
 

Change Paths In Reasoning !

on

  • 1,913 views

Presentation of my position paper published at the "New forms of reasoning" ISWC workshop.

Presentation of my position paper published at the "New forms of reasoning" ISWC workshop.

Statistics

Views

Total Views
1,913
Views on SlideShare
1,912
Embed Views
1

Actions

Likes
1
Downloads
33
Comments
0

1 Embed 1

http://www.linkedin.com 1

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Change Paths In Reasoning ! Change Paths In Reasoning ! Presentation Transcript

  • Change paths in reasoning! Raphael Volz FZI Forschungszentrum Informatik Universität Karlsruhe (TH) Karlsruhe, Germany 11.11.2007
  • Proposition
    • We need a consensus benchmark
    • Approximate is better than nothing
    • Tractable languages make speed
    • Incremental reasoning is smart
  • We need a consensus benchmark (1) Recent Performance Benchmark @ FZI Note: Joint work with Jürgen Bock, Qiu Ji, Peter Haase, Pellet performance close to Racer, Sesame preformance close to OWLIM Is this evaluation representative???
  • We need a consensus benchmark (2) Shortcomings of various benchmarks Source: Timo Weithörner et al., What‘s wrong with owl benchmarks, Proc. of 2nd int. Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS 2006)
  • Need for a consensus benchmark (3) Improvements Achieved with TREC Source: E. M. Voorhees, TREC: Improving Information Access through Evaluation, American Society for Information Science and Technology   Vol. 32, No. 1  Oct/Nov 2005 Consensus Metric Consensus Data Sets
  • Approximate is better than nothing (1) Ontologies in WATSON Corpus Source: Mathieu d‘Acquin et al., Characterizing Knowledge on the Semantic Web with Watson, EON 2007 Workshop, Busan, Korea We need to approximate with OWL DL reasoners
  • Approximate is better than nothing (2)
    • Idea derived from FOL work
    Source: Hitzler and Vrandecic, Resolution-based approximate reasoning for OWL DL, in Y. Gil et al. (Eds.): Proc. of ISWC 2005, LNCS 3729, pp. 383–397, 2005.
  • Approximate is better than nothing (3)
    • Idea derived from FOL work
    Source: Hitzler and Vrandecic, Resolution-based approximate reasoning for OWL DL, in Y. Gil et al. (Eds.): Proc. of ISWC 2005, LNCS 3729, pp. 383–397, 2005.
  • Approximate is better than nothing (3)
    • Syntactic approaches ( possibly unsound )
      • Stuckenschmidt & van Harmelen 2002
      • Wache, Groot, & Stuckenschmidt 2005
      • Hitzler & Vrandecic 2005
      • Groot, Stuckenschmidt & Wache 2005
      • Hurtado, Poulovassilis, & Wood 2006
    • Approaches based on Knowledge Compilation
      • Selman & Kautz 1991
      • Pan & Thomas 2007
  • Tractable languages make speed (1) Dez 2003 - DAML.ORG Corpus Source: Mathieu d‘Acquin et al., Characterizing Knowledge on the Semantic Web with Watson, EON 2007 Workshop, Busan, Korea Jul 2007 - WATSON Corpus Source: Raphael Volz, Web Ontology Reasoning with logic databases, dissertation, university of karlsruhe, 2004 Tractable Languages dominate (and will continue to do so)
  • Tractable languages make speed (2) Source: Markus Krötzsch, Sebastian Rudolph, and Pascal Hitzler; Complexity of Horn Description Logics Technical Report, Institute AIFB, University of Karlsruhe, 2007 Combined complexity of various DLs 1 1 1 1 3 # Available Reasoners (known to me)
  • Incremental reasoning is smart (1) Incremental answers is what we expect on the web Standard expectation for query answering on the web
  • Incremental reasoning is smart (2)
    • Alternate possible interpretations of incremental reasoning
      • Maintain state information from previous reasoning cycles when dealing with change to the KB (Pellet interpretation)
      • Provide answers / results incrementally (anytime behaviour)
    Incremental reasoning saves work Source: C. Halaschek-Wiener et al. Description Logic Reasoning for Dynamic A-Boxes, 2006 DL Workshop, CEUR WS 189
  • The ideal Semantic WEB reasoning approach time Quality as a combination of soundness and completness
    • Functional Qualities
    • Measurable quality
    • Recognizable quality
    • Monotonicity
    • Consistency
    • Diminishing returns
    • Interruptability
    • Preemtability
    Source: Shlomo Zilberstein, Using Anytime Algorithms in Intelligent Systems, AI Magazine, Fall 1996 HAPPY TO DISCUSS WITH YOU !!!