A comprehensive survey on travel recommender systems
Travelling is a combination of journey, transportation, travel-time, accommodation, weather,
events, and other aspects which are likely to be experienced by most of the people at some …
events, and other aspects which are likely to be experienced by most of the people at some …
A survey of recommendation systems
Today's internet is able to discover almost any product or piece of information. The large
amounts of unfiltered information returned by an internet query calls for filters able to …
amounts of unfiltered information returned by an internet query calls for filters able to …
[HTML][HTML] Restaurant recommender system based on sentiment analysis
Today, exploiting sentiment analysis has become popular in designing recommender
systems in various fields, including the restaurant and food area. However, most of the …
systems in various fields, including the restaurant and food area. However, most of the …
A deep recommendation model of cross-grained sentiments of user reviews and ratings
The matrix factorization model based on user-item rating data has been widely studied and
applied in recommender systems. However, data sparsity, the cold-start problem, and poor …
applied in recommender systems. However, data sparsity, the cold-start problem, and poor …
Restaurant recommendation system for user preference and services based on rating and amenities
Recommendation systems are being enforced to offer personalized set of services to the
users. They are basically build to produce recommendations or suggestions (like …
users. They are basically build to produce recommendations or suggestions (like …
Analyzing the impact of components of yelp. com on recommender system performance: case of Austin
S Lee, H Shin, I Choi, J Kim - IEEE Access, 2022 - ieeexplore.ieee.org
As people's demand for eating out is steadily increasing, the number of restaurants is
continuously increasing, and catering industry platforms such as Yelp, Open Table, and …
continuously increasing, and catering industry platforms such as Yelp, Open Table, and …
Incorporating multidimensional information into dynamic recommendation process to cope with cold start and data sparsity problems
Abstract Area-of-Interest (AOI) recommendation is a type of context-aware recommendation
that works based on location-based data. A context-aware recommender system should be …
that works based on location-based data. A context-aware recommender system should be …
Deep learning mechanism and big data in hospitality and tourism: Develo** personalized restaurant recommendation model to customer decision-making
With the increasing ubiquity of booking restaurants through online platforms, the need for
restaurant recommender systems that satisfy individual preferences has grown. Previous …
restaurant recommender systems that satisfy individual preferences has grown. Previous …
[HTML][HTML] Interest identification from browser tab titles: A systematic literature review
M Farina, M Kostin, G Succi - Computers in Human Behavior Reports, 2022 - Elsevier
Modeling and understanding users interests has become an essential part of our daily lives.
A variety of business processes and a growing number of companies employ various tools …
A variety of business processes and a growing number of companies employ various tools …
Competitive gamification in crowdsourcing-based contextual-aware recommender systems
YL Lin, ND Ding - International Journal of Human-Computer Studies, 2023 - Elsevier
During the COVID-19 outbreak, crowdsourcing-based context-aware recommender systems
(CARS) which capture the real-time context in a contactless manner played an important …
(CARS) which capture the real-time context in a contactless manner played an important …