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Multi-Criteria Recommendation Systems to Foster Online Grocery.
Manar Mohamed Hafez1, Rebeca P Díaz Redondo2, Ana Fernández Vilas2
1College of Computing and Information Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT)-Smart Village, Giza P.O. Box 12676, Egypt.
Sensors (Basel, Switzerland)
|June 2, 2021
Summary
This study enhances online grocery shopping recommendations by comparing bag-of-words (BOW) and Doc2Vec methods. Doc2Vec significantly improves product, package, and health-based recommendations, offering a better user experience.
Area of Science:
- Information Science
- Computer Science
- E-commerce Technology
Background:
- Information overload necessitates efficient user access mechanisms.
- Recommendation systems (RS) are intelligent solutions for personalized information delivery.
- RS are crucial in e-commerce for product suggestion and sales optimization.
Purpose of the Study:
- To address the challenge of insufficient product information in recommendation systems.
- To propose and evaluate three-criteria recommendation systems (product, package, health) for online grocery shopping.
- To compare the effectiveness of different document representation methods for product data.
Main Methods:
- Product data transformation using bag-of-words (BOW) and Doc2Vec (a neural network-based method).
- Development of three-criteria recommendation systems based on product composition, packaging, and health information.
- Evaluation through user and expert surveys to compare system performance.
Main Results:
- Doc2Vec document representation outperformed BOW in recommendation tasks.
- The three-criteria recommendation system demonstrated improved performance with Doc2Vec.
- Neural network-based methods significantly altered and improved recommendation outcomes.
Conclusions:
- Doc2Vec is a superior method for transforming product data in recommendation systems.
- A multi-criteria approach (product, package, health) enhances online grocery recommendations.
- Advanced methods like Doc2Vec offer significant improvements for e-commerce RS.
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