Behaviour classification for temporal data with limited readings - Fattah, Polla (2017)
Classifying items using temporal data, i.e. several readings of the same attribute in different time points, has many applications in the real world. The pivotal question which motivates this study is: ''Is it possible to quantify behavioural change in temporal data? And what is the best reference point to compare the behaviour change with?". The focus of this study will be in applications in economics such as playing many rounds of public goods games and share price moves in the stock market.