  Game developers benefit from availability of custom game genres when doing
game market analysis. This information can help them to spot opportunities in
market and make them more successful in planning a new game. In this paper we
find good classifier for predicting category of a game. Prediction is based on
description and title of a game. We use 2443 iOS App Store games as data set to
generate a document-term matrix. To reduce the curse of dimensionality we use
Latent Semantic Indexing, which, reduces the term dimension to approximately
1/9. Support Vector Machine supervised learning model is fit to pre-processed
data. Model parameters are optimized using grid search and 20-fold cross
validation. Best model yields to 77% mean accuracy or roughly 70% accuracy with
95% confidence. Developed classifier has been used in-house to assist games
market research.
