{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T18:57:42Z","timestamp":1787165862262,"version":"3.56.0"},"reference-count":37,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T00:00:00Z","timestamp":1774224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research, Development, and Innovation Authority (RDIA) of the Kingdom of Saudi Arabia","award":["13461-imamu-2023-IMIU-R-3-1-HW-"],"award-info":[{"award-number":["13461-imamu-2023-IMIU-R-3-1-HW-"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JTAER"],"abstract":"<jats:p>The rapid growth of digital tourism platforms has intensified information overload and decision complexity for both locals and travelers, while operators struggle to differentiate their offerings and sustain profitable, data-driven e-commerce models. This paper presents Doroob, a big data and artificial intelligence (AI)-driven, context-aware recommendation system that integrates traditional recommender techniques with real-time facial emotion recognition (FER) to enable intelligent tourism commerce. Doroob combines three AI-based recommendation strategies: smart adaptive recommendation (SAR) collaborative filtering, a Vowpal Wabbit-based context-aware model, and a LightFM hybrid model. It trained on datasets built from the Google Places API and enriched with ratings adapted from MovieLens. FER, implemented with DeepFace and OpenCV, analyzes short video segments as users browse destination details, converts emotion scores into 1\u20135 satisfaction ratings, and stores this implicit feedback alongside explicit ratings to support adaptive, emotion-aware personalization. Experimental results show that the context-aware model achieves the strongest top-K ranking performance, the hybrid LightFM model yields the highest AUC of 0.95, and the SAR model provides the most accurate rating predictions, demonstrating that combining contextual modeling and FER-based implicit feedback can enhance personalization, mitigate cold-start, and support data-driven promotion of local tourist services in intelligent e-commerce ecosystems.<\/jats:p>","DOI":"10.3390\/jtaer21030095","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T13:53:34Z","timestamp":1774274014000},"page":"95","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Emotion and Context-Aware Artificial Intelligence Recommendation for Urban Tourism"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6054-4534","authenticated-orcid":false,"given":"Mashael","family":"Aldayel","sequence":"first","affiliation":[{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4186-9805","authenticated-orcid":false,"given":"Abeer","family":"Al-Nafjan","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reman","family":"Alwadiee","sequence":"additional","affiliation":[{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah","family":"Altammami","sequence":"additional","affiliation":[{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abeer","family":"Alnafaei","sequence":"additional","affiliation":[{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leena","family":"Alzahrani","sequence":"additional","affiliation":[{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,23]]},"reference":[{"key":"ref_1","first-page":"167","article-title":"Tourism in Saudi Arabia","volume":"1","author":"Mufeed","year":"2014","journal-title":"Glob. 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