Abstract
Motivated by the ability that visualizations have for explaining complex relationships, we revisit an alternative and efficient algorithm for visualizing relationships between objects. QAPgrid was proposed to solve the problem of allocating objects in a grid. The algorithm uses as its mathematical model the NP-hard Quadratic Assignment Problem. We implemented an efficient Memetic Algorithm for solving the layout optimization problem. The algorithm has been previously tested on a variety of datasets with good results. In this chapter, we explore the algorithm’s potential for analysing social networks. In particular, we examined the collaboration network created around the artificial world of the Marvel Universe comic books. We show how the algorithm can generate accurate and informative visualizations for analysing complex graphs. Furthermore, to demonstrate an alternative use of the algorithm, we analyse and visualize products (wines) and customers (telecom clients). In doing so, we show how the algorithm is suitable for the analysis of different types of objects organized as a network.
Keywords
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The “datafication” concept is discussed by Kennet Neil Cukier and Viktor Mayer-Mayer-Schoenberger in “The Rise of Big Data”, Foreign Affairs, 2013.
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Acknowledgements
Pablo Moscato acknowledges previous support from the Australian Research Council Future Fellowship FT120100060 and Australian Research Council Discovery Projects DP120102576 and DP140104183.
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Lobos, C.S., de Vries, N.J., Inostroza-Ponta, M., Berretta, R., Moscato, P. (2019). Visualizing Products and Consumers: A Gestalt Theory Inspired Method. In: Moscato, P., de Vries, N. (eds) Business and Consumer Analytics: New Ideas. Springer, Cham. https://doi.org/10.1007/978-3-030-06222-4_16
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