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Spider monkey optimization (SMO) algorithm imitates the spider monkey's fission-fusion social behavior. It is evident through literature that the SMO is a competitive swarm-based algorithm that is used to solve difficult real-life problems. The SMO's search process is a little bit biased by the random component that drives it with high explorative searching steps. A hybridized SMO with a memetic search to improve the local search ability of SMO is proposed here. The newly developed strategy is titled Memetic SMO (MeSMO). Further, the proposed MeSMO-based clustering approach is applied to solve a big data problem, namely, the spam review detection problem. A customer usually makes decisions to purchase something or make an image of someone based on online reviews. Therefore, there is a good chance that the individuals or companies may write spam reviews to upgrade or degrade the stature or value of a trader/product/company. Therefore, an efficient spam detection algorithm, MeSMO, is proposed and tested over four complex spam datasets. The reported results of MeSMO are compared with the outcomes obtained from the six state-of-art strategies. A comparative analysis of the results proved that MeSMO is a good technique to solve the spam review detection problem and improved precision by 3.68%.

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Quick Response (QR) Code is very useful for encoding the data in an efficient manner. Here data capacity in 2D barcode is limited according to the various types of data formats used for encoding. The data in image format uses more space. The data capacity can be increased by compressing the data using any of the data compression techniques before encoding. In this paper, we suggest a technique for data compression which in turn helps to increase the data capacity of QR Codes generated for image. The main objective of this paper is to present how QR code can be utilized best in boarding pass for managing luggage at air port. Misplace of luggage at air port is very common; here we are proposing an idea for proper handling of misplaced luggage.