Customer segmentation using bisecting k-means algorithm based on recency, frequency, and monetary (RFM) model
نویسندگان
چکیده
منابع مشابه
Persistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm
Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...
متن کاملDesigning an Algorithm for Cancerous Tissue Segmentation Using Adaptive K-means Cluttering and Discrete Wavelet Transform
Background: Breast cancer is currently one of the leading causes of death among women worldwide. The diagnosis and separation of cancerous tumors in mammographic imagesrequire accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. Objective: This paper proposes a new algorithm which draws on discrete wavelet transform and adaptive ...
متن کاملDiscovering Active and Profitable Patterns with Rfm (recency, Frequency and Monetary) Sequential Pattern Mining–a Constraint Based Approach
Sequential pattern mining is an extension of association rule mining that discovers time-related behaviors in sequence database. It extends association by adding time to the transactions. The problem of finding association rules concern with intratransaction patterns whereas that of sequential pattern mining concerns with inter-transaction patterns. Generalized Sequential Pattern (GSP) mining a...
متن کاملStudy of Customer Segmentation for Auto Services Companies Based on RFM Model
This paper aims to explore the applicability of the RFM (Recentness,Frequency,Monetary) model in the customer segmentation of auto services companies, for which it obtains the weight of each index through the method of analytic hierarchy process (AHP) and segments the customers with K-means clustering method. This paper divides customers into several segments by comparing customer lifetime valu...
متن کاملA Fuzzy ANP Based Weighted RFM Model for Customer Segmentation in Auto Insurance Sector
Data mining has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the raw data. This study has proposed a brand new and practical fuzzy analytic network process (FANP) based weighted RFM (Recency, Frequency, Monetary value) model for application in K-means algorithm for auto insurance customers’ segmentation. The developed met...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Jurnal Teknologi dan Sistem Komputer
سال: 2019
ISSN: 2338-0403,2620-4002
DOI: 10.14710/jtsiskom.8.2.2020.78-83