This paper proposes a method that allows the clustering and identification of similarities
between users of a digital tourism platform, through the extraction of the sentiments …

Sažetak Nowadays, a huge amount of data is generated due to rapid Information and
Communication Technology development. In this paper, a digital banking strategy has been …

Targeted promotions in retail are becoming increasingly popular, particularly in UK grocery
retail sector, where competition is stiff and consumers remain price sensitive. Given this, a …

Effective management of customer's knowledge leads to efficient Customer Relationship
Management (CRM). To accurately predict customer's behaviour, clustering, especially K …

This paper investigates how clustering algorithms and Recency, Frequency, and Monetary
value (RFM) analysis can be performed on online transactions to provide strategies for …

Fuzzy C-mean (FCM) is the most well-known and widely-used fuzzy clustering algorithm.
However, one of the weaknesses of the FCM is the way it assigns membership degrees to …

The viability of every insurance company depends on risk assessment of new life policy
proposals. Machine learning techniques are increasingly shown to double case processing …

Online business competition is very tight. One strategy that can be done is to retain
customers. By applying the concept of CRM (Customer Relationship Management), the …

Customer segmentation and profiling has become an important marketing strategy in most
businesses as a preparation for better customer services as well as enhancing customer …

Purpose–The goal of this study is to identify the main clusters of bank customers in order to
help commercial banks to better identify their customers and design more efficient marketing …