An Information Recommendation Technique Based on Influence and Activeness of Users in Social Networks
Source abstract
Abstract
Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Recommender Systems and Techniques · Complex Network Analysis Techniques · Human Mobility and Location-Based Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science and Engineering, Ewha Womans University, Seoul 03760, Korea
Funding
Ewha Womans University
References (26)
Show source-provided references
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