Short text topic modeling techniques, applications, and performance: a survey
Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …
fundamental task since many real-world applications require semantic understanding of …
A survey of recommender systems with multi-objective optimization
Recommender systems have been widely applied to several domains and applications to
assist decision making by recommending items tailored to user preferences. One of the …
assist decision making by recommending items tailored to user preferences. One of the …
Six human-centered artificial intelligence grand challenges
Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the
human condition in ways that are not yet well understood. Negative unintended …
human condition in ways that are not yet well understood. Negative unintended …
Explainable AI in big data intelligence of community detection for digitalization e-healthcare services
Recommender Systems are designed to analysis the available data in the system to predict
user's desires and provide appropriate personalized suggestions to each user that suits their …
user's desires and provide appropriate personalized suggestions to each user that suits their …
Social recommendation: a review
Recommender systems play an important role in helping online users find relevant
information by suggesting information of potential interest to them. Due to the potential value …
information by suggesting information of potential interest to them. Due to the potential value …
A deep reinforcement learning based long-term recommender system
L Huang, M Fu, F Li, H Qu, Y Liu, W Chen - Knowledge-based systems, 2021 - Elsevier
Recommender systems aim to maximize the overall accuracy for long-term
recommendations. However, most of the existing recommendation models adopt a static …
recommendations. However, most of the existing recommendation models adopt a static …
Recommender systems for large-scale social networks: A review of challenges and solutions
Social networks have become very important for networking, communications, and content
sharing. Social networking applications generate a huge amount of data on a daily basis …
sharing. Social networking applications generate a huge amount of data on a daily basis …
Let me explain: Impact of personal and impersonal explanations on trust in recommender systems
Trust in a Recommender System (RS) is crucial for its overall success. However, it remains
underexplored whether users trust personal recommendation sources (ie other humans) …
underexplored whether users trust personal recommendation sources (ie other humans) …
Excessive use of online video streaming services: Impact of recommender system use, psychological factors, and motives
With the growing relevance of the Internet as a tool for communication and entertainment,
researchers have examined the effects of individual's psychological factors and media use …
researchers have examined the effects of individual's psychological factors and media use …
Social movie recommender system based on deep autoencoder network using Twitter data
H Tahmasebi, R Ravanmehr… - Neural Computing and …, 2021 - Springer
Recommender systems attempt to provide effective suggestions to each user based on their
interests and behaviors. These recommendations usually match the personal user …
interests and behaviors. These recommendations usually match the personal user …