Cluster-based information retrieval by using (K-means)-hierarchical parallel genetic algorithms approach

Cluster-based information retrieval is one of the information retrieval (IR) tools that organize, extract features and categorize the web documents according to their similarity. Unlike traditional approaches, cluster-based IR is fast in processing large datasets of document. To improve the quality of retrieved documents, increase the efficiency of IR and reduce irrelevant documents from user search. In this paper, we proposed a (K-means)-hierarchical parallel genetic algorithms approach (HPGA) that combines the K-means clustering algorithm with hybrid PG of multi-deme and master/slave PG algorithms. K-means uses to cluster the population to k subpopulations then take most clusters relevant to the query to manipulate in a parallel way by the two levels of genetic parallelism, thus, irrelevant documents will not be included in subpopulations, as a way to improve the quality of results. Three common datasets (NLP, CISI, and CACM) are used to compute the recall, precision, and F-measure averages. Finally, we compared the precision values of three datasets with Genetic-IR and classic-IR. The proposed approach precision improvements with IR-GA were 45% in the CACM, 27% in the CISI, and 25% in the NLP. While, by comparing with Classic-IR, (K-means)-HPGA got 47% in CACM, 28% in CISI, and 34% in NLP

Correct-by-Construction Approach for Formal Verification of IoT Architecture

International audienceMany disciplines have adopted component-based principles to avail themselves of the many advantages they bring, especially component reusability. In a short time, the component-based architecture became a renown branch in the IT world and the center of interest of many researchers. Much work has been conducted in this context for the verification of component-based applications (CBAs). However, the main focus has been on the structural aspect of such compositions, while the behavioral aspect has seldom been dealt with. In this paper, our goal is to close this gap and propose a formal approach to verify the behavioral correctness of CBAs. We first define a set of requirements to be satisfied by the structure and the behavior of a CBA, represented by a set of interactions that may occur between their components. Then, we build a formal Event-B model to represent these requirements in a rigorous and non-ambiguous way. The use of the Event-B refinement technique allows us to master the complexity of CBAs by introducing their elements in an incremental manner. The correctness of the development is ensured by establishing a set of proof obligations, under the Rodin platform, and also by animating it with the ProB animator/model checker. The approach is illustrated by a running example

Formal modelling and verification of scalable service composition in IoT environment

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