Online Popularity Prediction Scheme Based on Converging Property in Content Aware Soft Real Time Media Broadcast System
A small number of online popular contents are often clicked by a great quantity of users in a short period,and take the most of the wireless cellular network traffic.With popularity prediction,the popular contents would be broadcasted to the potential users for saving a lot of transmitting resource,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2015-11-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015221/ |
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| Summary: | A small number of online popular contents are often clicked by a great quantity of users in a short period,and take the most of the wireless cellular network traffic.With popularity prediction,the popular contents would be broadcasted to the potential users for saving a lot of transmitting resource,as illustrated in content aware soft real time media broadcast（CASoRT）system.With the data set collected from the Chinese commercial cellular network,the converging property of web contents,users and geographic positions in online news was shown.Then,two prediction schemes such as linear log and constant scaling model were proposed to estimate the popularity of online news,and improved by an optimal observation threshold.After comparison of simulation results,the linear log model performs better. |
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| ISSN: | 1000-0801 |