A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement

Minjuan WANG; Zhengpeng JI; Chao LV

doi:10.11959/j.issn.1000-0801.2016153

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A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement

Operating technology wide-angle | 更新时间：2024-06-05

- A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement
- Observation and communication Vol. 32, Issue 5, Pages: 160-165(2016)
- 作者机构：
  
  1. 江苏省公用信息有限公司，江苏南京 210006
  2. 中国电信股份有限公司智慧家庭运营中心，江苏南京 210006
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2016153
  CLC： TP181
- Published Online：2016-05，
  
  Published：20 May 2016
- 稿件说明：
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Minjuan WANG, Zhengpeng JI, Chao LV. A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement[J]. Observation and communication, 2016, 32(5): 160-165.
DOI：

Minjuan WANG, Zhengpeng JI, Chao LV. A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement[J]. Observation and communication, 2016, 32(5): 160-165. DOI： 10.11959/j.issn.1000-0801.2016153.

摘要

提出了一种符合用户行为的，基于海量IPTV用户特征数据，对IPTV用户进行分群和规则提取的算法模型。首先提出了符合用户点播使用行为的IPTV用户分群的描述维度，即通过基础属性描述用户分群、通过点播行为描述用户分群变化趋势。然后提出了预测度量值的概念，对用户分群的稳定性进行描述，并提出了对稳定的用户分群提取点播行为概率的算法。最后通过大量的IPTV运营数据对算法模型进行了验证分析。

Abstract

An algorithm model conformed to the user behavior

based on the massive IPTV user characteristic data which extract rules and classify IPTV users was proposed.First

IPTV user group description dimension in accordance with the user on demand was put forward.Namely

the user group could be described by basic property and trend of user behavior could be described by users' demand behavior.Then the concept of prediction measurement was put forward

the stability of user group was described

and an algorithm which extracted demand behavior probability on stable user group was proposed.At last

the algorithm model was verified and analyzed by massive IPTV operation data.

关键词

Keywords

references

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