Citation

Lam, Xin Yin and Ramasamy, R. Kanesaraj (2026) A Safety-Enhanced and Trust-Aware Recommendation Framework for Travel Companion Matching. Information, 17 (5). p. 406. ISSN 2078-2489

Text information-17-00406-v3.pdf - Published Version Restricted to Repository staff only Download (7MB)

Abstract

Travel companion matching presents unique challenges compared with conventional recommendation domains, as it involves real-world interpersonal interaction, perceived safety risks, and limited historical user data under cold-start conditions. Existing platforms often lack structured multi-factor matching and transparent integration of trust and safety constraints. This study makes three contributions. First, it introduces a methodology for deriving interpretable compatibility weights from user preference data under cold-start conditions. Second, it presents a four-algorithm comparative evaluation framework that identifies user-preferred matching strategies through controlled real-user testing. Third, it proposes a safety-enhanced empirical hybrid algorithm that integrates a hard trust gate (T ≥ 0.7), safety-oriented components (51.3% normalised weight), and empirically derived preference personalisation (48.7%) within a single scoring framework. A three-phase empirical methodology is adopted: Phase 1 (n = 26 survey) derives compatibility weights, revealing safety (69.2%), travel pace (76.9%), and budget (73.1%) as dominant factors; Phase 2 (n = 15) compares four algorithms, with safety-first matching receiving the highest acceptance rate (60.0%, 95% Wilson CI: 35.7–80.2%); Phase 3 (n = 13 journeys) evaluates the hybrid algorithm, achieving an 84.6% selection rate with Precision@6 = 0.333, MRR@6 = 0.554, and NDCG@6 = 0.597. These results provide preliminary evidence that trust-aware constraints can be integrated with empirically derived preference modelling to produce actionable recommendations under cold-start conditions, offering a reproducible approach for peer-to-peer travel platforms prioritising user safety.

Item Type:	Article
Uncontrolled Keywords:	Travel companion matchingt trust-aware recommender systems
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	05 Jun 2026 02:25
Last Modified:	05 Jun 2026 02:25
URII:	http://shdl.mmu.edu.my/id/eprint/15981

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