- Tytuł:
- Customer’s Purchase Prediction Using Customer Segmentation Approach for Clustering of Categorical Data
- Autorzy:
-
Singh, Juhi
Mittal, Mandeep - Powiązania:
- https://bibliotekanauki.pl/articles/1841413.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
categorical data
clustering algorithm
frequent pattern mining
association rules
customer relationship management - Opis:
- Traditional clustering algorithms which use distance between a pair of data points to calculate their similarity are not suitable for clustering of boolean and categorical attributes. In this paper, a modified clustering algorithm for categorical attributes is used for segmentation of customers. Each segment is then mined using frequent pattern mining algorithm in order to infer rules that helps in predicting customer’s next purchase. Generally, purchases of items are related to each other, for example, grocery items are frequently purchased together while electronic items are purchased together. Therefore, if the knowledge of purchase dependencies is available, then those items can be grouped together and attractive offers can be made for the customers which, in turn, increase overall profit of the organization. This work focuses on grouping of such items. Various experiments on real time database are implemented to evaluate the performance of proposed approach.
- Źródło:
-
Management and Production Engineering Review; 2021, 12, 2; 57-64
2080-8208
2082-1344 - Pojawia się w:
- Management and Production Engineering Review
- Dostawca treści:
- Biblioteka Nauki
Artykuł