A systematic literature review of sparsity issues in recommender systems
The tremendous expansion of information available on the web voraciously bombards
users, leaving them unable to make decisions and having no way of stepping back to …
users, leaving them unable to make decisions and having no way of stepping back to …
Robust collaborative filtering recommendation with user-item-trust records
The ever-increasing popularity of recommendation systems allows users to find appropriate
services without excessive effort. However, due to the unstable and complex network …
services without excessive effort. However, due to the unstable and complex network …
Combining review-based collaborative filtering and matrix factorization: A solution to rating's sparsity problem
An important factor affecting the performance of collaborative filtering for recommendation
systems is the sparsity of the rating matrix caused by insufficient rating data. Improving the …
systems is the sparsity of the rating matrix caused by insufficient rating data. Improving the …
Fake review detection in e-Commerce platforms using aspect-based sentiment analysis
P Hajek, L Hikkerova, JM Sahut - Journal of Business Research, 2023 - Elsevier
Consumers rely on internet user reviews. Existing sentiment-based detection systems fail to
capture consumer feelings regarding numerous aspects of products or services which …
capture consumer feelings regarding numerous aspects of products or services which …
A novel temporal recommender system based on multiple transitions in user preference drift and topic review evolution
C Wangwatcharakul, S Wongthanavasu - Expert Systems with Applications, 2021 - Elsevier
Recommender systems are challenging research problems being exploited to suggest new
items or services, such as books, music and movies, and even people, to users based on …
items or services, such as books, music and movies, and even people, to users based on …
A two-stage locality-sensitive hashing based approach for privacy-preserving mobile service recommendation in cross-platform edge environment
With the increasing popularity of service computing paradigm, tremendous resources or
services are emerging rapidly on the Web, imposing heavy burdens on the service selection …
services are emerging rapidly on the Web, imposing heavy burdens on the service selection …
A distributed locality-sensitive hashing-based approach for cloud service recommendation from multi-source data
To maximize the economic benefits, a cloud service provider needs to recommend its
services to as many users as possible based on the historical user-service quality data …
services to as many users as possible based on the historical user-service quality data …
[HTML][HTML] Exploring consumers' buying behavior in a large online promotion activity: The role of psychological distance and involvement
As a key marketing tool, online sales promotion has been widely used by online retailers to
increase sales of products and brands. Most previous researches on online sales promotion …
increase sales of products and brands. Most previous researches on online sales promotion …
Multi-dimensional quality-driven service recommendation with privacy-preservation in mobile edge environment
With the advance of mobile edge computing (MEC), the number of edge services running on
mobile devices grows explosively. In this situation, it is becoming a necessity to recommend …
mobile devices grows explosively. In this situation, it is becoming a necessity to recommend …
Privacy‐preserving and scalable service recommendation based on SimHash in a distributed cloud environment
With the increasing volume of web services in the cloud environment, Collaborative Filtering‐
(CF‐) based service recommendation has become one of the most effective techniques to …
(CF‐) based service recommendation has become one of the most effective techniques to …