Determination of the prioritized areas of graduate theses in industrial engineering with data mining

Nowadays, many theses are written at the master's or doctoral level. In this thesis, it is important for the universities to produce proactive solutions for the determination of the subjects of today's trends and the solution of the problems of the enterprises in the real sense. In this research, it has been discussed in the research by considering the title, summary and keywords of the master's and doctoral theses written under the roof of industrial engineering between 1975 and 2012 in YÖK thesis database. Downloaded thesis data are stored in MSSQL database. Theses are classified by Naive Bayes algorithm written in the scope of thesis study and BAGGING, J48, JRIP, KNN, NB, NBM, SMO algorithms which are ready in Weka program. The results of the study show that the number of thesis varies according to universities and periods. In addition, the theses included in the study are classified under the Optimization category with a maximum rate of 20.7%. The most successful classification algorithm for the emergence of this result was the KNN algorithm. However, 14% of all thesis studies have been published under the roof of Istanbul Technical University. This result was the university that made the most thesis study in the field of Industrial Engineering.