Name: Utilizing Embeddings to Learn a Universal Customer Behavior Representation in E-Commerce (en Inglés)
SKU: 66156805
Price: 95.47 USD
Availability: InStock
Author: Alves Gomes, Miguel

portada Utilizing Embeddings to Learn a Universal Customer Behavior Representation in E-Commerce (en Inglés)

Utilizing Embeddings to Learn a Universal Customer Behavior Representation in E-Commerce (en Inglés)

Formato

Libro Físico

Editorial

Springer Vieweg

Autor

Alves Gomes, Miguel

Idioma

Inglés

N° páginas

220

Encuadernación

Tapa Blanda

Dimensiones

21x14.8x1.4 cm

ISBN13

9783658507800

Utilizing Embeddings to Learn a Universal Customer Behavior Representation in E-Commerce (en Inglés)

Alves Gomes, Miguel (Autor) · Springer Vieweg · Tapa Blanda

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Reseña del libro "Utilizing Embeddings to Learn a Universal Customer Behavior Representation in E-Commerce (en Inglés)"

E-commerce operates in a highly dynamic and competitive environment, where customer satisfaction is key to success. Delivering personalized experiences at scale requires systems capable of reliably modeling individual customer behavior while respecting privacy and data protection constraints such as the GDPR. This book proposes a universal, privacy-compliant customer representation that is task-agnostic and incrementally adaptable. A decoupled three-stage approach is introduced, combining self-supervised learning of customer embeddings from behavioral data with flexible downstream models for predicting customer intentions. Temporal extensions improve performance, particularly under sparse information conditions, while lifelong learning enables dynamic adaptation to new interactions and evolving product spaces without full retraining.Comprehensive experiments across multiple real-world e-commerce datasets demonstrate consistent performance improvements over state-of-the-art baselines. By decoupling personalization from personal data, this work offers a scalable and privacy-preserving foundation for next-generation personalization systems.