Abstract
The integration of two of the biggest giants in the computing world has resulted in the development and advancement of new methodologies in data processing. Cognitive computing and big data analytics are integrated to give rise to advanced technologically sound algorithms like MOIWO and NSGA. There is an important role played by the E-projects portfolio selection (EPPS) issue in the web development environment that is handled with the help of a decision making algorithm based on big data. The EPPS problem tackles choosing the right projects for investment on the social media in order to achieve maximum return at minimal risk conditions. In order to address this issue and further optimize EPPS probe on social media, the proposed work focuses on building a hybrid algorithm known as NSGA-II-MOIWO. This algorithms makes use of the positive aspects of MOIWO algorithm and NSGA-II algorithm in order to develop an efficient one. The experimental results are recorded and analyzed in order to determine the most optimal algorithm based on the return and risk of investment. Based on the results, it is found that NSGA-II-MOIWO outperforms both MOIWO and NSGA, proving to be a better hybrid alternative.
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