Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/32500
Title: | Customer Interaction Networks Based on Multiple Instance Similarities | Authors: | FUENTES HERRERA, Ivett NAPOLES RUIZ, Gonzalo Arco, Leticia VANHOOF, Koen |
Issue Date: | 2020 | Source: | Business Information Systems, p. 279 -290 | Series/Report: | Lecture Notes in Business Information Processing | Abstract: | Understanding customer behaviors is deemed crucial to improve customers' satisfaction and loyalty, which eventually is materialized in increased revenue. This paper tackles this challenge by using complex networks and multiple instance reasoning to examine the network structure of Customer Purchasing Behaviors. Our main contributions rely on a new multiple instance similarity to measure the interaction among customers based on the mutual information theory focuses on the customers' bags, a new network construction approach involving customers, orders and products, and a new measure for evaluating its internal consistency. The simulations using 12 real-world problems support the effectiveness of our proposal. | Document URI: | http://hdl.handle.net/1942/32500 | ISBN: | 978-3-030-53336-6 978-3-030-53337-3 |
DOI: | 10.1007/978-3-030-53337-3_21 | Category: | C1 | Type: | Proceedings Paper | Validations: | vabb 2022 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Ivett Fuentes BIS 2020 Paper 30.pdf Restricted Access | Published version | 478.7 kB | Adobe PDF | View/Open Request a copy |
Page view(s)
84
checked on Jun 9, 2022
Download(s)
4
checked on Jun 9, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.