[HTML][HTML] How do context-aware artificial intelligence algorithms used in fitness recommender systems? A literature review and research agenda
P Venkatachalam, S Ray - International Journal of Information Management …, 2022 - Elsevier
Recommender Systems (RS) help the user in the decision-making process when there is a
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
[HTML][HTML] Leveraging social influence based on users activity centers for point-of-interest recommendation
Abstract Recommender Systems (RSs) aim to model and predict the user preference while
interacting with items, such as Points of Interest (POIs). These systems face several …
interacting with items, such as Points of Interest (POIs). These systems face several …
MORec: At the crossroads of context-aware and multi-criteria decision making for online music recommendation
Context-aware recommender systems have received considerable attention from industry
and academic areas. In this paper, we pay heed to the growing interest in integrating context …
and academic areas. In this paper, we pay heed to the growing interest in integrating context …
FS-MLC: Feature selection for multi-label classification using clustering in feature space
Multi-label classification (MLC) has attracted many researchers in the field of machine
learning as it has a straightforward problem statement with varied solution approaches. Multi …
learning as it has a straightforward problem statement with varied solution approaches. Multi …
Kt-cdulf: Knowledge transfer in context-aware cross-domain recommender systems via latent user profiling
Recommender systems are crucial in today's digital world, by enhancing user engagement
experience in digital ecosystems. Internet of things (IoT) have huge potential to generate …
experience in digital ecosystems. Internet of things (IoT) have huge potential to generate …
Mining top-N high-utility operation patterns for taxi drivers
C Liu, C Guo - Expert Systems with Applications, 2021 - Elsevier
In recent years, the rapid development of mobile network and wireless sensor technology
has brought opportunities to change the way of the existing taxi business operation. How to …
has brought opportunities to change the way of the existing taxi business operation. How to …
Dynamic collaborative filtering based on user preference drift and topic evolution
C Wangwatcharakul, S Wongthanavasu - IEEE Access, 2020 - ieeexplore.ieee.org
Recommender systems are efficient tools for online applications; these systems exploit
historical user ratings on items to make recommendations of items to users. This paper aims …
historical user ratings on items to make recommendations of items to users. This paper aims …
CDRec-CAS: cross-domain recommendation using context-aware sequences
Recommender Systems (RSs) are a subclass of information filtering systems. RSs assist
users in choosing interesting items from an extensive collection of items. This article …
users in choosing interesting items from an extensive collection of items. This article …
CD-SemMF: Cross-domain semantic relatedness based matrix factorization model enabled with linked open data for user cold start issue
Personalized recommendations to cold start user is one of the significant challenges in
information filtering systems. Most of the existing systems inherited the idea of collaborative …
information filtering systems. Most of the existing systems inherited the idea of collaborative …
Analyzing the Impact of Domain Similarity: A New Perspective in Cross-Domain Recommendation
Cross-domain recommendation (CDR) has recently emerged as an effective way to alleviate
the cold-start and sparsity issues faced by recommender systems, by transferring information …
the cold-start and sparsity issues faced by recommender systems, by transferring information …