Spark-based Distributed Multi-features Hybrid IPTV Viewing Implicit Feedback Scoring Model

被引：2

作者：

Yue Jin ^{[1
]}

Gu Junhua ^{[1
]}

Zhang Suqi ^{[2
]}

Zhang Jian ^{[1
]}

机构：

[1] Hebei Univ Technol, Sch Comp Sci & Engn, Tianjin 300130, Peoples R China

[2] Tianjin Univ Commerce, Sch Informat Engn, Tianjin 300134, Peoples R China

来源：

8TH INTERNATIONAL CONFERENCE ON ADVANCES IN INFORMATION TECHNOLOGY | 2017年 / 111卷

关键词：

user viewing behaviors; implicit feedback; multi-features; Spark;

D O I：

10.1016/j.procs.2017.06.046

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, in order to improve IPTV recommendation system, a Spark-based IPTV implicit feedback scoring model is proposed based on the characteristics of user viewing behaviors. Firstly, this paper analyzes the data types and characteristics of IPTV user viewing behaviors. Secondly, this paper presents a new multi-features hybrid implicit feedback scoring model framework based on viewing duration and viewing ratio. Then, we design and implement the distributed multi-features hybrid implicit feedback scoring model on Spark cluster. Finally, we figure out reasonable weights of different features of implicit feedback through experiment. And the experiment shows that the Spark-based model performs better in time efficiency. (C) 2015 The Authors. Published by Elsevier B.V.

引用

页码：441 / 447

页数：7

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