MMIROct 9, 2014

Recommendation Scheme Based on Converging Properties for Contents Broadcasting

arXiv:1410.2324v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses energy efficiency in content broadcasting for wireless network users, but it appears incremental as it builds on existing models with specific data.

The paper tackled the problem of efficiently broadcasting popular videos in wireless networks by analyzing a content propagation model based on user behavior, location, and converging properties, and proposed a recommendation scheme that achieved high energy efficiency.

Popular videos are often clicked by a mount of users in a short period. With content recommendation, the popular contents could be broadcast to the potential users in wireless network, to save huge transmitting resource. In this paper, the contents propagation model is analyzed due to users' historical behavior, location, and the converging properties in wireless data transmission, with the users' communication log in the Chinese commercial cellular network. And a recommendation scheme is proposed to achieve high energy efficiency.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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