Speeding Up Ontology-Based Free-Form Service Request Recognition

We offered, in a previous paper, an ontology-based approach to recognize constraints in free-form service requests and provide services for users. Our system handles a service request by finding, from among many ontologies, the domain ontology that best matches the request and then uses the matched ontology to generate the service request constraints. Although our system is powerful in recognizing constraints and therefore servicing requests, the recognition process is a bottleneck due to the number of the tested ontologies and the amount of computations involved. This paper provides a novel approach to speed up the recognition process by (1) using ontology indexing and (2) excluding inapplicable regular expressions early in the process and thus reducing the number of applied regular expressions. Our experiments show that our techniques are effective in significantly reducing the amount of computations and therefore speeding up the recognition process.

Optimization of function by method of random research directed by probabilities

This research aims to establish algorithm to optimize a function (calculate of lower limit) by random method. We have found algorithm that called algorithm of moving triangles. This algorithm have been experimented on a wide set of functions, and these experiments proved that algorithm is very useful in exploring the lower limit.