INFERENCE ENGINES

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INFERENCE ENGINES

• Semantic Web
• CrossUp Project
• Prepared by Gizem Olgu

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Inference Engines

• Inference engines necessary for the processing of
  the knowledge available in the semantic web
• Inference engine is a software tool that deduces
  new knowledge (fact) from already known knowledge
  using inference rules.
• Inference rules controls the inference steps,
  which the inference engine makes.

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Inference Engines

• For instance
• Grandfather (Tom, Marry) Father (Tom, Jack)
  Father (Jack, Marry)
• Here there are two facts,
• Tom is the father of Jack
• Jack is the father of Marry,
• Rule is when you find a new relationship where
  Tom is a father of Jack and then if for that Jack
  there is a Marry for which Jack is the father of
  Marry, then new knowledge is Tom is a grandfather
  of Marry.

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Inference Engines

• There are two types of inferencing,
• forward chaining
• backward chaining
• The backward chaining inference engines tries to
  prove a goal by establishing the truth of its
  conditions
• i.e. the rule if A and B then C, the backward
  chaining engine will try to prove C by first
  proving A and then proving B. Proving these
  conditions to be true, may well invoke further
  calls to the engine and so on.

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Inference Engines

• The forward chaining inference engine takes rule,
  and if its conditions are true, adds its
  conclusion to working memory, until no more rules
  can be applied
• i.e. if the conditions of the rule if A and B
  then C are true, then C is added to working
  memory.
• In forward chaining the system simply test the
  rules in the order that occurs, therefore rule
  order is important.

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Inference Engines

• Many inference engines use forward chaining
  method since the forward chaining is
• much simpler
• much faster, because no overhead of dynamically
  determining, which rule to activate.
• There are many inference engines and some of them
  are used in semantic web applications.

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Inference Engines

• Example of inference engines
• F-OWL
• is an inference engine for semantic web.
• is an inference engine for OWL language.
• is based on XSB and Flora-2 system and takes
  advantage of lots of advanced features of both
  systems.
• F-OWL uses a frame based approach to reason with
  OWL ontologies.

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Inference Engines

• Example of inference engines
• Jena
• is a java framework for building semantic web
  applications.
• It provides a programmatic environment for RDF,
  RDFS and OWL, including a rule-based inference
  engine.
• Jena is open source and grown out of work with
  the HP labs semantic web programmer.

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Inference Engines

• Example of inference engines
• RACER
• is a semantic web inference engine for
• developing ontologies,
• query answering over RDF documents and with
  respect to specified RDFS/DAML and OWL
  ontologies,
• registering permanent queries (e.g., for building
  a document management system) with notification
  of new results if available.

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Inference Engines

• As a conclusion,
• The inference engine is the component in your
  Semantic Web application that takes semantics and
  ontology definitions and goes on to deduce
  relationships and handle queries.
• The inference engine for semantic web is an
  active field of experimental research area and as
  inference engines improve and become more
  powerful, applications of the semantic web will
  provide increased benefit to the users.

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REFERENCES(General information about inference
engines.)

• http//www.semanticweb.org/inference.html
• This reference gives explanation about Inference
  Engine for semantic web.
• http//www.rt-sys.com/ie.htm
• This reference gives explanation about an
  Inference Engine.
• http//www.w3.org/DesignIssues/Rules.html
• Rules and Facts Inference engines vs. Web, this
  is explain part of the relationship between the
  Semantic Web and inference engines, either
  existing or legacy, and discuss the relationship
  between inference rules and logical facts.

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REFERENCES(General information about inference
engines.)

• http//www.amzi.com/ExpertSystemsInProlog/02usingp
  rolog.htm
• Building Expert Systems in Prolog. Prolog
  interpreter is an inference engine.
• Prolog has a built-in backward chaining inference
  engine which can be used to partially implement
  some expert systems.
• Prolog rules are used for the knowledge
  representation, and the Prolog inference engine
  is used to derive conclusions. Other portions of
  the system, such as the user interface, must be
  coded using Prolog as a programming language.

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REFERENCES(General information about inference
engines.)

• http//www.w3.org/TandS/QL/QL98/pp/queryservice.ht
  ml
• A Query and Inference Service for RDF
• www.agfa.com/w3c/2002/02/thesis/thesis.pdf
• An inference engine for RDF

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REFERENCES(Some inference engine)

• http//fowl.sourceforge.net/ and for information
  www.csee.umbc.edu/yzou1/publications/faabs.pdf
• F-OWL
• http//www.hpl.hp.com/semweb/jena2.htm
• Jena
• http//www.cs.concordia.ca/haarslev/racer/ and
  for information http//km.aifb.uni-arlsruhe
  .de/ws/eon2003/ EON2003_Haarslev.pdf
• RACER

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REFERENCES(Some inference engine)

• http//www.agfa.com/w3c/euler/
• Euler is an inference engine supporting logic
  based proofs. It is a backward-chaining reasoner
  enhanced with Euler path detection and will tell
  you whether a given set of facts and rules
  supports a given conclusion.

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REFERENCES(Some inference engine)

• http//sourceforge.net/projects/eulersharp
• EulerSharp is an inference engine supporting
  logic based proofs. It is a backward-chaining
  reasoner enhanced with Euler path detection and
  will tell you whether a given set of facts and
  rules supports a given conclusion. It is
  interoperable with W3C Cwm. - Sourceforge
  EulerSharp project.

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THANKS.