Abstract
Automatically generated data mining tools namely artificial neural networks, support vector machines and fuzzy rule-based classifiers, using different term weighting schemes as data pre-processing techniques for opinion mining problems are presented. Developed collective nature-inspired self-tuning meta-heuristic for solving unconstrained and constrained real- and binary-parameter optimization problems called Co-Operation of Biology Related Algorithms was used for classifiers design. Three Opinion Mining problems from DEFT’07 competition were solved by proposed classifiers. Obtained results were compared between themselves and with results obtained by methods which were proposed by other researchers. As the result, workability and usefulness of designed classifiers were established and best data processing approach for them was found.
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The reported study was funded by Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Region Science and Technology Support Fund to the research project No 16-41-243064\(\backslash \)16.
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Akhmedova, S., Semenkin, E., Stanovov, V. (2018). Co-operation of Biology Related Algorithms for Solving Opinion Mining Problems by Using Different Term Weighting Schemes. In: Madani, K., Peaucelle, D., Gusikhin, O. (eds) Informatics in Control, Automation and Robotics . Lecture Notes in Electrical Engineering, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-319-55011-4_4
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