Approaches and algorithms to mitigate cold start problems in recommender systems: a systematic literature review

DK Panda, S Ray - Journal of Intelligent Information Systems, 2022 - Springer
Cold Start problems in recommender systems pose various challenges in the adoption and
use of recommender systems, especially for new item uptake and new user engagement …

A bibliometric review on the development in e-tourism research

S Singh, A Bashar - International Hospitality Review, 2021 - emerald.com
Purpose E-tourism is instilling in the tourism industry with the advancement in the
technological infrastructure all over the world and fetching tremendous tourists' attention …

Investigating online social media users' behaviors for social commerce recommendations

SH Liao, R Widowati, YC Hsieh - Technology in Society, 2021 - Elsevier
Online social media create virtual communities and network platforms that people use to
create, share, and exchange opinions, views and experiences. With social networks, social …

Multi-view graph attention network for travel recommendation

L Chen, J Cao, Y Wang, W Liang, G Zhu - Expert Systems with Applications, 2022 - Elsevier
As an e-commerce feature, the recommender system can enhance the consumer shopping
experience and create huge benefits for businesses. The e-tourism has become one of the …

Personalized tourism recommendations and the E-tourism user experience

X Yang, L Zhang, Z Feng - Journal of Travel Research, 2024 - journals.sagepub.com
Previous research indicates that personalized tourism recommendation (PTR) is becoming
increasingly important in tourism marketing. However, many areas of PTR remain …

Multi-objective reinforcement learning approach for trip recommendation

L Chen, G Zhu, W Liang, Y Wang - Expert Systems with Applications, 2023 - Elsevier
Trip recommendation is an intelligent service that provides personalized itinerary plans for
tourists in unfamiliar cities. It aims to construct a series of ordered POIs that maximizes user …

Exploring an efficient POI recommendation model based on user characteristics and spatial-temporal factors

C Xu, D Liu, X Mei - Mathematics, 2021 - mdpi.com
The advent of mobile scenario-based consumption popularizes and gradually maturates the
application of point of interest (POI) recommendation services based on geographical …

Personalized travel recommendation: a hybrid method with collaborative filtering and social network analysis

JL Chang, H Li, JW Bi - Current Issues in Tourism, 2022 - Taylor & Francis
This study proposes a hybrid method for producing personalized travel recommendation that
better meet travellers' individual needs and also improve their online booking experience …

Context-aware recommendation systems in the IoT environment (IoT-CARS)–A comprehensive overview

D Nawara, R Kashef - IEEE Access, 2021 - ieeexplore.ieee.org
An essential goal of recommendation systems is to provide users with accurate and
personalized recommendations that meet their preferences. With the rapid growth of IoT …

Keywords-enhanced deep reinforcement learning model for travel recommendation

L Chen, J Cao, W Liang, J Wu, Q Ye - ACM Transactions on the Web, 2022 - dl.acm.org
Tourism is an important industry and a popular entertainment activity involving billions of
visitors per annum. One challenging problem tourists face is identifying satisfactory products …