On the Need for Configurable Travel Recommender Systems: A Systematic Mapping Study

TL;DR

This paper systematically analyzes travel recommender systems to highlight the lack of configuration support for diverse contexts, emphasizing the need for adaptable solutions to improve recommendation relevance and development efficiency.

Contribution

It provides a comprehensive mapping study revealing the gap in configurable support for TRSs across different contexts, guiding future research in this area.

Findings

Most TRSs lack configuration support for diverse contexts

Current TRSs are often built from scratch for each specific environment

Identified challenges suggest need for adaptable configuration methodologies

Abstract

Travel Recommender Systems TRSs have been proposed to ease the burden of choice in the travel domain by providing valuable suggestions based on user preferences Despite the broad similarities in functionalities and data provided by TRSs these systems are significantly influenced by the diverse and heterogeneous contexts in which they operate This plays a crucial role in determining the accuracy and appropriateness of the travel recommendations they deliver For instance in contexts like smart cities and natural parks diverse runtime informationsuch as traffic conditions and trail status respectivelyshould be utilized to ensure the delivery of pertinent recommendations aligned with user preferences within the specific context However there is a trend to build TRSs from scratch for different contexts rather than supporting developers with configuration approaches that promote reuse minimize errors and accelerate timetomarket To illustrate this gap in this paper we conduct a systematic mapping study to examine the extent to which existing TRSs are configurable for different contexts The conducted analysis reveals the lack of configuration support assisting TRSs providers in developing TRSs closely tied to their operational context Our findings shed light on uncovered challenges in the domain thus fostering future research focused on providing new methodologies enabling providers to handle TRSs configurations