[HTML][HTML] Neuromarketing: a review of research and implications for marketing
In this research, we reviewed existing studies which used neuromarketing techniques in
various fields of research. The results revealed that most attempts in neuromarketing have …
various fields of research. The results revealed that most attempts in neuromarketing have …
[HTML][HTML] Artificial intelligence in recommender systems
Recommender systems provide personalized service support to users by learning their
previous behaviors and predicting their current preferences for particular products. Artificial …
previous behaviors and predicting their current preferences for particular products. Artificial …
A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques
Improving the efficiency of methods has been a big challenge in recommender systems. It
has been also important to consider the trade-off between the accuracy and the computation …
has been also important to consider the trade-off between the accuracy and the computation …
A literature review of recommender systems in the television domain
D Véras, T Prota, A Bispo, R Prudêncio… - Expert Systems with …, 2015 - Elsevier
Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions of relevant items to users. These systems have received increasing attention …
suggestions of relevant items to users. These systems have received increasing attention …
A multi-criteria collaborative filtering recommender system for the tourism domain using Expectation Maximization (EM) and PCA–ANFIS
In order to improve the tourist experience, recommender systems are used to offer
personalized information for online users. The hotel industry is a leading stakeholder in the …
personalized information for online users. The hotel industry is a leading stakeholder in the …
A hybrid recommender system for e-learning based on context awareness and sequential pattern mining
The rapid evolution of the Internet has resulted in the availability of huge volumes of online
learning resources on the web. However, many learners encounter difficulties in retrieval of …
learning resources on the web. However, many learners encounter difficulties in retrieval of …
An e-learning recommendation approach based on the self-organization of learning resource
S Wan, Z Niu - Knowledge-Based Systems, 2018 - Elsevier
In e-learning, most content-based (CB) recommender systems provide recommendations
depending on matching rules between learners and learning objects (LOs). Such learner …
depending on matching rules between learners and learning objects (LOs). Such learner …
Multi-criteria recommender systems
G Adomavicius, N Manouselis, YO Kwon - Recommender systems …, 2010 - Springer
This chapter aims to provide an overview of the class of multi-criteria recommender systems.
First, it defines the recommendation problem as a multicriteria decision making (MCDM) …
First, it defines the recommendation problem as a multicriteria decision making (MCDM) …
Travelers decision making using online review in social network sites: A case on TripAdvisor
Digital technology and social media have brought numerous benefits to human society.
TripAdvisor, which runs on user-generated content, provides a platform for travelers to …
TripAdvisor, which runs on user-generated content, provides a platform for travelers to …
A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor. com
Decision support models for satisfactory restaurants have attracted numerous researchers'
attention. Many extant models do not consider the active, neutral and passive information in …
attention. Many extant models do not consider the active, neutral and passive information in …