**7. Conclusions and Future Work**

Games in the digital era promote cultural heritage by relying on several affective capabilities. This article has a twofold focus. First, a template Simon–Ando iterative scheme is developed for clustering player profiles consisting of attributes with affective content. Certain schemes deriving from this template are evaluated based on inter- and intra-clustering distances as well as on the number of iterations and the number of floating point operations required. The former are indicators of clustering quality, while the latter of scalability. The results are interpreted in light of the Bartle taxonomy. Understanding the player base in this way can lead to recommendations about placing emphasis on specific game elements. Second, the role of user annotations on clustering is evaluated by deriving versions using weight matrices based on them. Experiment results clearly show that in every case the inclusion of user annotations had a distinct positive effect.

Concerning future research directions, the algorithmic aspect of the proposed methodology can be improved by examining alternative combinations of attributes and tensors utilizing them. Moreover, the stability properties as well as its complexity should be carefully evaluated through extensive simulations. Another possible research direction lies in constructing more datasets from diverse player audience. This will lead to better evaluation of alternative player clustering methodologies.

**Author Contributions:** G.D. did the coding and developed the algorithmic strategy; Y.V. contributed to the algorithmic approach and did the bibliographic search; and P.M. provided guidance and oversight. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was co-financed by the European Union and Greek national funds through the Competitiveness, Entrepreneurship and Innovation Operational Programme, under the Call "Research-Create-Innovate"; project title: "Development of technologies and methods for cultural inventory data interoperability—ANTIKLEIA"; project code: T1EDK-01728; MIS code: 5030954.

**Conflicts of Interest:** The authors declare no conflict of interest.

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