Katia Lida Kermanidis, Kostas Anagnostou


Modeling the semantic space of a complex dynamic domain, like an action game, by automatically identifying the relations governing the game’s concepts, entities, actions and other features, is a challenging research objective. In this paper we propose modeling the semantic space of the action game SpaceDebris, in order to identify semantic similarities between players’ gaming styles. To this end we employ Latent Semantic Analysis and attempt to identify latent underlying semantic information governing the various gaming techniques. The several challenging research issues that arise when attempting to apply Latent Semantic Analysis to non-textual data describing a complex dynamic problem space (defining the semantic vocabulary and “word” utterances, deciding upon the dimensionality reduction rate, etc.) are addressed, and the framework of the proposed experimental setup is described. The extracted similarities are further employed for player modelling, i.e. grouping players according to their playing styles.


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Paper Citation

in Harvard Style

Kermanidis K. and Anagnostou K. (2010). LSA-BASED SEMANTIC REPRESENTATION OF ACTION GAMES . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010) ISBN 978-989-8425-29-4, pages 218-223. DOI: 10.5220/0003082602180223

in Bibtex Style

author={Katia Lida Kermanidis and Kostas Anagnostou},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2010)
SN - 978-989-8425-29-4
AU - Kermanidis K.
AU - Anagnostou K.
PY - 2010
SP - 218
EP - 223
DO - 10.5220/0003082602180223