Improved scatter search algorithm based on meerkat clan algorithm to solve NP-hard problems

A modified Scatter Search (SS) algorithm based on Meerkat Clan Algorithm (MCA) has been presented in this paper. SS is one of the important metaheuristic algorithms, while the MCA is one of the recent swarm intelligence algorithms. The modified SS algorithm, including the main steps of MCA, through it the diversity and exploration of SS-MCA's solutions, have improved. The proposed algorithm has been applied to two important NP-Hard problems (Travelling Salesman Problem (TSP) and Flexible Job Shop Scheduling Problem (FJSSP)) to verify the performance of SS-MCA. The experimental results show that the performance of SS-MCA is better than both SS and MCA, respectively

Arguments extraction for e-health services based on text mining tools

The task of recognizing arguments and their components in text is known as argument extraction. Most arguments might be broken down into a petition and at least one premise that support it. A method to extract arguments is suggested in this work. The major words which are of high importance in arguments extraction were included in the suggested method on the basis of Arabic lexicon. The lexicon tool was used to apply classic text mining stages. The dataset, which includes over 3000 petitions, was collected from the Citizen Affairs Department in the Ministry of Health-Iraq. In addition, the experimental results exhibit that the suggested method extracts arguments from collected dataset with a 93.5% accuracy ratio