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Theses slides describe the principles of semantic networks (or triples) as a general and flexible representation format. We introduce the notion of deduction rules / inferences on semantic networks / triples. The detailed design of an inference engine -forward chaining- is introduced. It uses the so-called "delta driven computing" to optimise inference. The gereralization to forward chaining is provided, using the "Alexander Method". Principles of the implementation in Java are introduced, with appropriate methods on matrix operations, inparticular relational Join operations. FInally, we show how we can implement "Complex Event processing" and trigger mechanisms.