چکیده مقاله
One of the best tools for learning or mastering a language by students is to use vocabulary crossword puzzles It is desired to put as many words as possible on a small sized puzzle However, designing a compact crossword puzzle using a limited vocabulary is a complex task that usually requires manual participation In this study, we report the successful application of multi objective evolutionary optimization algorithms to generate compact crosswords The algorithm tries to find the best possible words from the predefined vocabulary such that the required space for the puzzle is minimized, i e , more words can be placed in a compact puzzle The whole process is automatic and at the end of the algorithm, the set of puzzle keys and clues on the Pareto front of the algorithm solution are generated The effectiveness of the proposed method is proved through a real word experiment to generate crossword puzzles from a vocabulary in the field of computer science
کلیدواژهها
نویسندگان
Reza Mortazavi
School of Engineering, Damghan University, Damghan, Iran;
Ali Mottaghi
School of Engineering, Damghan University, Damghan, Iran;
شیوه ارجاع
Mortazavi, Reza and Mottaghi, Ali,1398,Automatic compact vocabulary crossword generator using multi-objective evolutionary optimization,3rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی محاسبات نرم29 آبان 1398 · رودسر