Knowledge Representation Clause Samples

Knowledge Representation. In order to realistically model the domains we employ several ontologies. We developed an OWL ontology to represent the WS-Agreement schema. This ontology contains the concepts from the schema such as Guarantee, Scope, and ServiceLevelObjective with relationships between them. In addition to the significant elements from the WS-Agreement, we have also included the common predicates from the WSLA specification [25]. We allow the user to add additional predicates to this ontology to preserve flexibility. An instance of this ontology is created for each agreement that is introduced into the system where they can be queried and reasoned easily. Most of the guarantees are asserted over quality of service (QoS) concepts; therefore the QoS ontology as described in [12] defines such concepts as failureRate, latency, throughput, availability, and responseTime. In addition to these ontologies a third OWL ontology represents domain specific knowledge. For our scenario in e-commerce and its implementation we are using the RosettaNet ontology (▇▇▇▇://▇▇▇▇▇.▇▇.▇▇▇.▇▇▇/projects/meteor- s/wsdl-s/ontologies/rosetta.owl), also represented in OWL. Depending on the application, alternative or additional domain ontologies could be used. Finally, we use the OWL time [14] ontology to represent temporal concepts such as endTime, interval, dayOfWeek, and seconds. These ontologies are used to provide a commonality of terms between agreement parties and to provide rich domain knowledge to the search engine so that it may achieve the best possible match results. and hasType(P, “PercentageLessThanThreshold”) and hasPercentage(E, percent) do: if (percent<=x) then assert hasType(P, “less”) else assert hasType(P, “greater”) The above ARL rule looks for any expression which contains the predicate “PercentageLessThanThreshold” and if the percentage less than x it changes the predicate to “less” otherwise it changes it to “greater”. In many cases the value of x is dependent upon the parameter. For example, a user may require a high percentage for responseTime but may be more lenient about other parameters. This feature can be further customized by adding additional statements in the when segment which perform parameter checks. Predicate=percentageLessThanThreshold Parameter=”qos:responseTime” Value=5 Percent=99 Unit=”time:Seconds Predicate=less Parameter= qos:responseTime Value=6 Unit=”time:Seconds Predicate=less Parameter= qos:responseTime Value=6 Unit=”time:Seconds Ontologies are loaded i...