Abstract Currently available Collaborative Filtering (CF) algorithms often utilize user
behavior data to generate recommendations. The similarity calculation between users is …

Recommendation models for network information that are generally based on user ratings
fail to utilize user online behaviours such as reviews and likes, which indicate users' …

Aiming at the problems of traditional method of exercise recommendation precision, recall
rate, long recommendation time, and poor recommendation comprehensiveness, this study …

In order to ensure the quality of resource recommendation and solve the problems of low
recommendation accuracy, long recommendation time, and high data loss rate in the …

Currently, available collaborative filtering (CF) algorithms often utilize user behavior data to
generate recommendations. The similarity calculation between users is mostly based on the …

High‐quality vocational education is a vital basis for China's efforts to develop high‐quality
teachers and technical and skilled workers. The increasing development of contemporary …

Prior studies mostly consider outliers as noise data and eliminate them, resulting in the loss
of outlier knowledge. Based on the existing technology of recommendation systems and …

Context-aware recommender systems (CARS) are a key component in businesses, notably
in the e-transactions domain, since they assume that reviews, ratings, demographics, and …

The vigorous development of tourism has made rural tourism a highlight of the new era. In
order to better realize the classification of rural tourism features, this paper proposes a …

Location-based application services and location privacy protection solutions are often
required for the storage, management, and efficient retrieval of large amounts of geolocation …