This report presents our solution to PAKDD 2007 Data Mining Competition, which details the steps to develop the customer growth model to identify cross-selling opportunities. This model is able to score the propensity of a credit card customer to take up a home loan with the finance company. We first describe the data preparation steps in detail. Then, the home loan customer growth model is pro...

In this paper we present a system that tracks customers in a store and performs a number of activity analysis tasks based on the output from the tracker. We obtain the trajectories by employing a human body tracking system designed as a Bayesian jump-diffusion filter. The customer travel trajectories on the floor map are extracted and post processed to remove noise. The shoppers that belong to ...

Since mobile commerce is a new commerce mode, there is a significant meaning to research on customer satisfaction with its services. This paper evaluates the customer satisfaction with m-commerce services, which adopts ASCI model, uses AHP to identify the weight and adapts grey clustering relational method, and illustrates this method by an example. It makes an exploratory research on the appli...

Load forecasting plays a critical role in Smart Grid. As there have been various types of customers with different behaviours in a Smart Grid, it would benefit load forecasting if customer behaviours were taken into consideration. This paper proposes a novel load forecasting method that efficiently explores customers’ power consumption behaviours through learning. Our method uses L1-CCRF to ini...

The aim of the data mining process is to extract information from a large data set and transform it into an understandable structure for further use. Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships,...

Clustering is a widely studied data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this chapter, we will provide a detailed survey of the problem of text clustering. We will study the key challenges of the clustering problem, as it applies to the...

Clustering is a widely studied data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this chapter, we will provide a detailed survey of the problem of text clustering. We will study the key challenges of the clustering problem, as it applies to the...

Studying about the customer segmentation and begetting customer ranking plan diverts more attention in recent years. In this regard, this study tries on providing a methodology for segmenting customers based on their value driver parameters which extracted from transaction data and then ranks customers with regard to their customer lifetime value (CLV) score. Discovering hidden pattern between ...

In a transitioning word, specially in mall property industry, winning strategy comes from anticipating with people needs and desires, understanding them the most holistic way possible. The 7P marketing mix refined by Booms Bitner 1981 which consists of elements Product, Price, Place, Promotion, People, Physical evidence, Processes additional Partnerships, is tool for analyzing existing market c...