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Weighted Slotted RuleML for Similarity Matching in AgentMatcher Information Agents

Weighted Slotted RuleML for Similarity Matching in AgentMatcher Information Agents. Harold Boley , NRC IIT e-Business Virendra Bhavsar , UNB, Faculty of Computer Science. 2 November 2002 Revised: 26 February 2005. Slotted RuleML Via the Name-Giving Metarole slot (I).

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Weighted Slotted RuleML for Similarity Matching in AgentMatcher Information Agents

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  1. Weighted Slotted RuleML forSimilarity Matching in AgentMatcher Information Agents Harold Boley, NRC IIT e-Business Virendra Bhavsar, UNB, Faculty of Computer Science 2 November 2002 Revised: 26 February 2005

  2. Slotted RuleML Via the Name-Giving Metarole slot (I) Here is a self-explaining 'metarole' (slot) representationof the slotted, RDF-like Jess fact (automobile (make Ford) (model Explorer) (year 1999)) in Object-Oriented (OO) RuleML – part of RuleML 0.88 –with user slots named via the first subelement: <Atom> <opr><Rel>automobile</Rel></opr> <slot><Ind>make</Ind><Ind>Ford</Ind></slot> <slot><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot><Ind>year</Ind><Ind>1999</Ind></slot> </Atom> RuleML 0.88

  3. Slotted RuleML Via the Name-Giving Metarole slot (II) This 'Slotted RuleML' notation corresponds to the 'positionalized' ruleml-datalog notation <Atom> <opr><Rel>automobile</Rel></opr> <Ind>Ford</Ind> <Ind>Explorer</Ind> <Ind>1999</Ind> </Atom> if the 'roles' of the make, model, and year positions are remembered somewhere else (signature declaration) RuleML 0.88

  4. Slotted RuleML Via the Name-Giving Metarole slot (III) Note that a mix of an ordered sequence of args androle-unordered args will thus be possible in facts as well: <Atom> <opr><Rel>automobile</Rel></opr> <Ind>Ford</Ind> <Ind>Explorer</Ind> <Ind>1999</Ind> <slot><Ind>mileage</Ind><Ind>65000</Ind></slot> <slot><Ind>color</Ind><Ind>white</Ind></slot> </Atom> Also, Ind elements can be replaced by (typed) Var elements in all of the positional, slotted and mixed notations RuleML 0.88

  5. Extending Slotted RuleML for Weighted AgentMatcher Keyphrases AgentMatcher’s weighted keyphrases as Jess-likerole-weighted fact: (automobile (make 0.7 Ford) (model0.1 Explorer) (year0.2 1999)) Weighted Object-Oriented (WOO) RuleML –part of RuleML0.88– extends user slots by an XML attribute for such weights: <Atom> <opr><Rel>automobile</Rel></opr> <slot weight="0.7"><Ind>make</Ind><Ind>Ford</Ind></slot> <slot weight="0.1"><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot weight="0.2"><Ind>year</Ind><Ind>1999</Ind></slot> </Atom> RuleML 0.88

  6. Role-Weighted Slotted RuleML Queries for AgentMatcherSimilarity Matching AgentMatcher agent can then use a Jess-likerole-weighted query: (automobile (make 0.5 Ford) (model0.1 Explorer) (year0.4 Y)) RuleML 0.88 can use a corresponding query, and similaritymatching with the above fact succeeds, binding Y = 1999: <Atom> <opr><Rel>automobile</Rel></opr> <slot weight="0.5"><Ind>make</Ind><Ind>Ford</Ind></slot> <slot weight="0.1"><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot weight="0.4"><Ind>year</Ind><Var>Y</Var></slot> </Atom> RuleML 0.88

  7. Flat Feature Terms in Slotted RuleML The minimal 'metarole' (slot) representation of the slotted,RDF-like (untyped) feature term, similar to F-logic term, auto[make -> Ford; model -> Explorer; year -> 1999] in RuleML 0.88 with user slots named via the first subelement: <Cterm> <opc><Ctor>auto</Ctor></opc> <slot><Ind>make</Ind><Ind>Ford</Ind></slot> <slot><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot><Ind>year</Ind><Ind>1999</Ind></slot> </Cterm> Can also be used as an argument in facts RuleML 0.88

  8. Nested Feature Terms in Slotted RuleML The representation of the nested (untyped) feature term vehicle[winter -> auto[make -> Ford; model -> Explorer; year -> 1999] summer -> cycle[make -> Honda; model -> Magna; year -> 2002]] in RuleML 0.88 with user slots named via the first subelement: <Cterm> <opc><Ctor>vehicle</Ctor></opc> <slot><Ind>winter</Ind> <Cterm> <opc><Ctor>auto</Ctor></opc> <slot><Ind>make</Ind><Ind>Ford</Ind></slot> <slot><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot><Ind>year</Ind><Ind>1999</Ind></slot> </Cterm> </slot> <slot><Ind>summer</Ind> <Cterm> <opc><Ctor>cycle</Ctor></opc> <slot><Ind>make</Ind><Ind>Honda</Ind></slot> <slot><Ind>model</Ind><Ind>Magna</Ind></slot> <slot><Ind>year</Ind><Ind>2002</Ind></slot> </Cterm> </slot> </Cterm> RuleML 0.88

  9. Flat Weighted Feature Terms in Slotted RuleML for AgentMatcher Keyphrases Representation of AgentMatcher’s weights in an extended feature term: auto[make -0.7-> Ford; model -0.1-> Explorer; year -0.2-> 1999] RuleML 0.88 user slots can again be extended by an XML attribute for capturing weights: <Cterm> <opc><Ctor>auto</Ctor></opc> <slot weight="0.7"><Ind>make</Ind><Ind>Ford</Ind></slot> <slot weight="0.1"><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot weight="0.2"><Ind>year</Ind><Ind>1999</Ind></slot> </Cterm> Can also be used as an argument in facts RuleML 0.88

  10. Nested Weighted Feature Terms inSlotted RuleML for AgentMatcher Trees Representation of AgentMatcher’s weights in a nested feature term: vehicle[winter -0.6-> auto[make -0.7-> Ford; model -0.1-> Explorer; year -0.2-> 1999] summer -0.4-> cycle[make -0.5-> Honda; model -0.2-> Magna; year -0.3-> 2002]] RuleML 0.88 with the XML attribute for capturing weights: <Cterm> <opc><Ctor>vehicle</Ctor></opc> <slot weight="0.6"><Ind>winter</Ind> <Cterm> <opc><Ctor>auto</Ctor></opc> <slot weight="0.7"><Ind>make</Ind><Ind>Ford</Ind></slot> <slot weight="0.1"><Ind>model</Ind><Ind>Explorer</Ind></slot> <slot weight="0.2 "><Ind>year</Ind><Ind>1999</Ind></slot> </Cterm> </slot> <slot weight="0.4"><Ind>summer</Ind> <Cterm> <opc><Ctor>cycle</Ctor></opc> <slot weight="0.5"><Ind>make</Ind><Ind>Honda</Ind></slot> <slot weight="0.2"><Ind>model</Ind><Ind>Magna</Ind></slot> <slot weight="0.3"><Ind>year</Ind><Ind>2002</Ind></slot> </Cterm> </slot> </Cterm> RuleML 0.88

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