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A review on customer segmentation methods for personalized customer targeting in e-commerce use cases
The importance of customer-oriented marketing has increased for companies in recent
decades. With the advent of one-customer strategies, especially in e-commerce, traditional …
decades. With the advent of one-customer strategies, especially in e-commerce, traditional …
A hybrid approach using oversampling technique and cost‐sensitive learning for bankruptcy prediction
The diagnosis of bankruptcy companies becomes extremely important for business owners,
banks, governments, securities investors, and economic stakeholders to optimize the …
banks, governments, securities investors, and economic stakeholders to optimize the …
Functional framework for multivariant e-commerce user interfaces
A Wasilewski - Journal of Theoretical and Applied Electronic …, 2024 - mdpi.com
Modern e-businesses heavily rely on advanced data analytics for product recommendations.
However, there are still untapped opportunities to enhance user interfaces. Currently, online …
However, there are still untapped opportunities to enhance user interfaces. Currently, online …
A hybrid big data analytical approach for analyzing customer patterns through an integrated supply chain network
SC Wang, YT Tsai, YS Ciou - Journal of Industrial Information Integration, 2020 - Elsevier
The recent technology innovation such as big data and its applications has been adopted
widely in industries in order to deal with massive datasets. Through data integration, data …
widely in industries in order to deal with massive datasets. Through data integration, data …
[HTML][HTML] Space–time series clustering: Algorithms, taxonomy, and case study on urban smart cities
This paper provides a short overview of space–time series clustering, which can be
generally grouped into three main categories such as: hierarchical, partitioning-based, and …
generally grouped into three main categories such as: hierarchical, partitioning-based, and …
Customer Segmentation Model using K-means Clustering on E-commerce
A Agrawal, P Kaur, M Singh - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Customer segmentation is often referred to as dividing a market into groups of customers
who may share similar characteristics. This is an effective way to identify unmet customer …
who may share similar characteristics. This is an effective way to identify unmet customer …
Potential buyer identification and purchase likelihood quantification by mining user-generated content on social media
Understanding the purchase likelihood of potential buyers is an important prerequisite for
marketers to carry out targeted marketing. Massive authentic and personalized user …
marketers to carry out targeted marketing. Massive authentic and personalized user …
Sequential classification of customer behavior based on sequence-to-sequence learning with gated-attention neural networks
L Zhao, Y Zuo, K Yada - Advances in Data Analysis and Classification, 2023 - Springer
During the last decade, an increasing number of supermarkets have begun to use RFID
technology to track consumers' in-store movements to collect data on their shop** …
technology to track consumers' in-store movements to collect data on their shop** …
An improved intuitionistic fuzzy c-means for ship segmentation in infrared images
F Yang, Z Liu, X Bai, Y Zhang - IEEE Transactions on Fuzzy …, 2020 - ieeexplore.ieee.org
Infrared ship segmentation is extensively applied in military fields. Due to noise and intensity
inhomogeneity, the segmentation of infrared ship is a challenging task. The fuzzy c-means …
inhomogeneity, the segmentation of infrared ship is a challenging task. The fuzzy c-means …
Spectral clustering of customer transaction data with a two-level subspace weighting method
Finding customer groups from transaction data is very important for retail and e-commerce
companies. Recently, a “Purchase Tree” data structure is proposed to compress the …
companies. Recently, a “Purchase Tree” data structure is proposed to compress the …