Predicting the behaviour of customers is challenging, but important for service oriented businesses. Data mining techniques are used to make such predictions, typically using only recent static data. In this paper, a sequence mining approach is proposed, which allows taking historic data and temporal developments into account as well. In order to form a combined classifier, sequence mining is combined with decision tree analysis. In the area of sequence mining, a tree data structure is extended with hashing techniques and a variation of a classic algorithm is presented. The combined classifier is applied to real customer data and produces promising results.
Sequence Mining for Customer Behaviour Predictions in Telecommunications
|Autor:||Frank Eichinger, Detlef D. Nauck, Frank Klawonn|
Proceedings of the Workshop on Practical Data Mining: Applications, Experiences and Challenges, Berlin, Germany, 2006