Personalized trip recommendation with poi availability and uncertain traveling time
As location-based social network (LBSN) services become increasingly popular, trip
recommendation that recommends a sequence of points of interest (POIs) to visit for a user …
recommendation that recommends a sequence of points of interest (POIs) to visit for a user …
Trip recommendation meets real-world constraints: POI availability, diversity, and traveling time uncertainty
As location-based social network (LBSN) services become increasingly popular, trip
recommendation that recommends a sequence of points of interest (POIs) to visit for a user …
recommendation that recommends a sequence of points of interest (POIs) to visit for a user …
POI recommendation through cross-region collaborative filtering
Recommending points of interest (POIs) to a user according to the user's current location
and past check-in activities is the focus in this paper. Previously proposed probabilistic and …
and past check-in activities is the focus in this paper. Previously proposed probabilistic and …
Adaptive personalized recommender system using learning automata and items clustering
The personalized recommender systems provide user-related services based on user
preferences; these preferences are recorded in an individual profile. Therefore, the more …
preferences; these preferences are recorded in an individual profile. Therefore, the more …
Dynamic user profile for adaptive personalized recommender system using learning automata
The personalized recommender systems provide favorite services based on user
preferences and interests. Due to the user's interests changing over time; hence the …
preferences and interests. Due to the user's interests changing over time; hence the …
Recommendations based on user effective point-of-interest path
G Zhou, S Zhang, Y Fan, J Li, W Yao, H Liu - International Journal of …, 2019 - Springer
Abstract Point-of-interest (POI) recommendation has become an important service in
location-based social networks. Existing recommendation algorithms provide users with a …
location-based social networks. Existing recommendation algorithms provide users with a …
Movie recommender systems made through tag interpolation
QN Nguyen, N Duong-Trung, DN Le Ha… - Proceedings of the 4th …, 2020 - dl.acm.org
20 years of MovieLens datasets have witnessed a blossom of research that is garnering a
remarkable significance with the advent of e-commerce and the whole industry. Four …
remarkable significance with the advent of e-commerce and the whole industry. Four …
Improving recommender systems with rich side information
C Zhang - 2015 - summit.sfu.ca
Recommender systems have become extremely popular in recent years since they can
provide personalized information to user from a large amount of data, which is typically noisy …
provide personalized information to user from a large amount of data, which is typically noisy …
Sentimental feature based collaborative filtering recommendation
J Cao, W Li - 2017 IEEE International Conference on Big Data …, 2017 - ieeexplore.ieee.org
Taking advantage of online customer reviews for recommendation system is becoming
increasingly important in e-commerce field due to rich implication information of reviews. By …
increasingly important in e-commerce field due to rich implication information of reviews. By …
Towards evaluating user profiling methods based on explicit ratings on item features
LL Costanzo, Y Deldjoo, MF Dacrema… - arXiv preprint arXiv …, 2019 - arxiv.org
In order to improve the accuracy of recommendations, many recommender systems
nowadays use side information beyond the user rating matrix, such as item content. These …
nowadays use side information beyond the user rating matrix, such as item content. These …