Being a popular social network type, online dating sites provide a platform for people to find partners for establishing a relationship. In this study, a recommendation engine for one of the prominent online dating sites of Turkey is developed. It works as a support system to suggest potential matches to the site users. As opposed to the traditional systems that match users based on their revealed preferences, the engine is based on a rule set extracted from the past communication data, using association rule mining. A list of best matches based on scoring derived from these rules is presented. The performance of the engine is statistically tested. It is found that the scores of matching couples are found to be significantly higher than the non-matched couples' scores.

This study is carried out in Management Information System (MIS) department which accepts students from general and vocational high schools with widely varying range of educational backgrounds. As an emerging interdisciplinary field, MIS education demands both technical and managerial skills from its students. However, students with different backgrounds have to pursue the same diversified set of courses. The aim of this study is to investigate students' segments and profiles based on the various dimensions of academic abilities they possess, by performing cluster analysis. The data set consists of the student official grade for the required courses. First, dimensionality of the course grades is reduced to a few independent abilities by performing factor analysis. The summed scales representing the independent factors are then used in the cluster analysis to obtain student segments. Finally, variation of the student background measured by high school type is profiled for each segment. The students from general high schools have been more successful in MIS education compared to students from vocational schools where only the basic knowledge on management or computer skills is offered. The results of this analysis are also utilized in shaping various macro and micro level strategies in our MIS department.

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