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
This paper defines an advanced methodology for modeling applications based on Data Mining methods th...
Telecommunication sector generates a huge amount of data due to increasing number of subscribers, ra...
Sequences play a major role in the extraction of information from data. As an example, in business i...
As markets have become increasingly saturated, companies have acknowledged that their business strat...
[[abstract]]Most existing data mining algorithms apply data-driven data mining technologies. The maj...
Customer churn is one of the most critical issues faced by the telecommunications industry. In the t...
These days telecommunication sector has grown significantly due to the use of smart technologies, an...
The object of research is the process of analyzing the customer churn of telecommunications companie...
The object of research is the process of analyzing the customer churn of telecommunications companie...
We investigate the length of event sequence giving best predictions when using a continuous HMM app...
In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inher...
Abstract — The sequential sequence mining takes time interval between various transactions. Here we ...
In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inher...
In the telecom industry, large-scale of data is generated on daily basis by an enormous amount of cu...
From a data mining perspective, sequence classification is to build a classifier using frequent sequ...
This paper defines an advanced methodology for modeling applications based on Data Mining methods th...
Telecommunication sector generates a huge amount of data due to increasing number of subscribers, ra...
Sequences play a major role in the extraction of information from data. As an example, in business i...
As markets have become increasingly saturated, companies have acknowledged that their business strat...
[[abstract]]Most existing data mining algorithms apply data-driven data mining technologies. The maj...
Customer churn is one of the most critical issues faced by the telecommunications industry. In the t...
These days telecommunication sector has grown significantly due to the use of smart technologies, an...
The object of research is the process of analyzing the customer churn of telecommunications companie...
The object of research is the process of analyzing the customer churn of telecommunications companie...
We investigate the length of event sequence giving best predictions when using a continuous HMM app...
In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inher...
Abstract — The sequential sequence mining takes time interval between various transactions. Here we ...
In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inher...
In the telecom industry, large-scale of data is generated on daily basis by an enormous amount of cu...
From a data mining perspective, sequence classification is to build a classifier using frequent sequ...
This paper defines an advanced methodology for modeling applications based on Data Mining methods th...
Telecommunication sector generates a huge amount of data due to increasing number of subscribers, ra...
Sequences play a major role in the extraction of information from data. As an example, in business i...