Recommendation for online social feeds by exploiting user response behavior. Authors: Ping-Han Soh, Yu-Chieh Lin, and Ming-Syan ChenAuthors Info & Claims. WWW ...
Active users spend hours communicating with each other via these networks such that an enormous amount of data is created every second. The tremendous amount of ...
May 17, 2013 · user by exploiting the user's response behavior. We extract data from the most popular social network, and the experi- mental results show ...
A new approach to recommend interesting messages for each user by exploiting the user's response behavior is proposed, and the experimental results show ...
Recommendation for Online Social Feeds by Exploiting. User Response Behavior. Ping-Han Soh. Graduate Inst. of. Communication Engineering. National Taiwan ...
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What is social media recommendation?
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Feb 20, 2024 · Ping-Han Soh, Yu-Chieh Lin, Ming-Syan Chen: Recommendation for online social feeds by exploiting user response behavior.
In this study, we particularly present a complete design of a recommender method by analyzing both user interaction and user behavior in a social network.
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May 15, 2024 · Should they rely on creating recommendations based on interests that they know the user to possess (exploitation) or should they make ...
Mar 9, 2023 · The algorithms driving social media are called recommender systems. These algorithms are the engine that makes Facebook and YouTube what they are.
Mar 19, 2024 · Recommendation algorithms for social media feeds often function as black boxes from the perspective of users. We aim to detect whether social ...