By Hendrik Blockeel, Matthijs van Leeuwen, Veronica Vinciotti
This e-book constitutes the refereed convention lawsuits of the thirteenth overseas convention on clever facts research, which used to be held in October/November 2014 in Leuven, Belgium. The 33 revised complete papers including three invited papers have been conscientiously reviewed and chosen from 70 submissions dealing with all types of modeling and research equipment, without reference to self-discipline. The papers disguise all features of clever facts research, together with papers on clever aid for modeling and interpreting info from complicated, dynamical systems.
Read or Download Advances in Intelligent Data Analysis XIII: 13th International Symposium, IDA 2014, Leuven, Belgium, October 30 – November 1, 2014. Proceedings PDF
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Extra info for Advances in Intelligent Data Analysis XIII: 13th International Symposium, IDA 2014, Leuven, Belgium, October 30 – November 1, 2014. Proceedings
We examine the convergence of the heuristic search technique and estimate and evaluate a number of stopping criterion. The paper reports the results of extensive experiments conducted on our comprehensive time-series dataset and provides evidence to support our proposed techniques. Keywords: Software module clustering, modularisation, SBSE, seeding, timeseries, fitness function. 1 Introduction Large software systems tend to have complex structures that are often difficult to comprehend due to the large number of modules and inter-relationships that exist between them.
Structured Design. Prentice Hall (1979) 8. : Automatic clustering of software systems using a genetic algorithm. In: IEEE Proceedings STEP 1999 Software Technology and Engineering Practice, pp. 73–81 (1999) 9. : A new representation and crossover operator for search based optimization of software modularization. In: Proc. Genetic and Evolutionary Computation Conference, pp. 1351–1358. Morgan Kaufmann Publishers (2002) 10. : Search-based software engineering: Trends, techniques and applications.
However, for future work, we look to obtain a better estimate of the number of clusters. We also look to obtain the number of clusters from the dataset and compute the probabilities whilst running the process. In addition, in this paper, we have An Approach to Controlling C the Runtime for Search Based Modularisation 35 othesis, introduced in Section IV, works empirically; hoowdemonstrated that our hypo ever for future work we wiill include the formalised mathematical proof of the claaim. Furthermore, we aim to compare the techniques and approaches proposed in this paper against more systems an nd perform a more systematic comparison.