We investigate the issue of predicting new customers as profitable based on information about existing customers in a business-to-business environment. In particular, we show how latent semantic concepts from textual information of existing customers’ websites can be used to uncover...

To improve ATMs’ cash demand forecasts, this paper advocates the prediction of cash demand for groups of ATMs with similar day-of-the week cash demand patterns. We first clustered ATM centers into ATM clusters having similar day-of-the week withdrawal patterns. To retrieve...

This approach introduces idea mining as process of extracting new and useful ideas from unstructured text. We use an idea definition from technique philosophy and we focus on ideas that can be used to solve technological problems.<br> The rationale for the idea mining approach is taken over from...

The planning of technological research and development (R&D) is demanding in areas with many relationships between technologies. To support decision makers of a government organization with R&D planning in these areas, a methodology to make the technology impact more transparent is introduced....

Longitudinal consumer behavior has been modeled by sequence analysis. A popular application involves Acquisition Pattern Analysis exploiting typical acquisition patterns to predict a customer’s next purchase. Typically, the acquisition process is represented by an extensional, unidimensional...

Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain. Unfortunately, to date, it is unable to handle...

Although most data mining (DM) models are complex and general in nature, the implementation of such models in specific environments us often subject to practical constraints (e.g. budget constraints) or thresholds (e.g. only mail to customers with an expected profit higher than the investment...

The acquisition process of consumer durables is a ‘sequence’ of purchase events. Priority-pattern research exploits this ‘sequential order’ to describe a prototypical acquisition order for durables. This paper adds a predictive perspective to increase managerial relevance. Besides order...

The inability to capture sequential patterns is a typical drawback of predictive classification methods. This caveat might be overcome by modeling sequential independent variables by sequence-analysis methods. Combining classification methods with sequenceanalysis methods enables classification...

Random Forests (RF) is a successful classifier exhibiting performance comparable to Adaboost, but is more robust. The exploitation of two sources of randomness, random inputs (bagging) and random features, make RF accurate classifiers in several domains. We hypothesize that methods other than...