AIMED - A personalized TV recommendation system

被引：0

作者：

Hsu, Shang H. ^{[1
,2
]}

Wen, Ming-Hui ^{[1
]}

Lin, Hsin-Chieh ^{[1
]}

Lee, Chun-Chia ^{[1
]}

Lee, Chia-Hoang ^{[2
]}

机构：

[1] Natl Chiao Tung Univ, Dept Ind Engn & Management, 1001 Ta Hsueh Rd, Hsinchu, Taiwan

[2] Natl Chiao Tung Univ, Dept Comp Sci, Hsinchu, Taiwan

来源：

INTERACTIVE TV: A SHARED EXPERIENCE, PROCEEDING | 2007年 / 4471卷

关键词：

TV program recommendation system; predictor; personal information; lifestyle; activity; interest; mood;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Previous personalized DTV recommendation systems focus only on viewers' historical viewing records or demographic data. This study proposes a new recommending mechanism from a user oriented perspective. The recommending mechanism is based on user properties such as Activities, Interests, Moods, Experiences, and Demographic information-AIMED. The AIMED data is fed into a neural network model to predict TV viewers' program preferences. Evaluation results indicate that the AIMED model significantly increases recommendation accuracy and decreases prediction errors compared to the conventional model.

引用

页码：166 / +

页数：2

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