Practical Challenges in Indoor Mobile Recommendation

TL;DR

This paper discusses the practical challenges of developing indoor mobile recommendation systems, emphasizing variables like location and user interests, and aims to guide practitioners in choosing suitable approaches and technologies.

Contribution

It provides a systematic review and case analysis of indoor mobile recommendation challenges, offering practical guidance for implementation.

Findings

Identifies key variables affecting indoor recommendations

Highlights challenges in data collection and user interaction

Suggests best practices for system design and notification methods

Abstract

Recommendation systems are present in multiple contexts as e-commerce, websites, and media streaming services. As scenarios get more complex, techniques and tools have to consider a number of variables. When recommending services/products to mobile users while they are in indoor environments next to the object of the recommendation, variables as location, interests, route, and interaction logs also need to be taken into account. In this context, this work discusses the practical challenges inherent to the context of indoor mobile recommendation (e.g., mall, parking lot, museum, among others) grounded on a case and a systematic review. With the presented results, one expects to support practitioners in the task of defining the proper approach, technology, and notification method when recommending services/products to mobile users in indoor environments.