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Journal ArticleDOI

An integrated approach to renew software contract using machine learning.

TLDR
In this article, a machine-learning-based approach was used to set up an efficient process for contract renewal in a large-scale industrial environment, where the contract renewal is critical to maintaining a company's recurring revenue source.
Abstract
Contract renewal is critical to maintaining a company’s recurring revenue source. Therefore, there is a significant emphasis on setting up an efficient process for renewal. In this study, a machine...

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References
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Journal ArticleDOI

dbscan: Fast Density-Based Clustering with R

TL;DR: In this article, the authors describe the implementation and use of the R package dbscan, which provides complete and fast implementations of the popular density-based clustering algorithm DBSCAN and the augmented ordering algorithm OPTICS.
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Customer churn prediction by hybrid neural networks

TL;DR: Two hybrid models by combining two different neural network techniques for churn prediction, which are back-propagation artificial neural networks (ANN) and self-organizing maps (SOM) are considered.
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Customer churn prediction in telecommunications

TL;DR: The experimental results show that the new features with the six modelling techniques are more effective than the existing ones for customer churn prediction in the telecommunication service field.
Journal ArticleDOI

Price Fairness: Good and Service Differences and the Role of Vendor Costs

TL;DR: In this article, the authors argue that the perceived fairness of the price increase will also depend on the alignability of the cost and price increases, such that alignable increases will be perceived as more acceptable than nonalignable increases.
Journal ArticleDOI

Customer churn prediction in the telecommunication sector using a rough set approach

TL;DR: This study proposes an intelligent rule-based decision-making technique, based on rough set theory (RST), to extract important decision rules related to customer churn and non-churn, and shows that RST based on GA is the most efficient technique for extracting implicit knowledge in the form of decision rules from the publicly available, benchmark telecom dataset.