Towards Personalized Video Summarization using Synchronized Comments and Probabilistic Latent Semantic Analysis

被引：0

作者：

Chung, Cheng-Tao ^{[1
]}

Hsiung, Hsin-Kuan ^{[2
]}

Wei, Cheng-Kuang ^{[1
]}

Lee, Lin-shan ^{[2
]}

机构：

[1] Natl Taiwan Univ, Grad Inst Elect Engn, Taipei, Taiwan

[2] Natl Taiwan Univ, Grad Inst Commun Engn, Taipei, Taiwan

来源：

2014 IEEE 3RD GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE) | 2014年

关键词：

Video Summary; Personalization; PLSA; Machine Learning; Unsupervised Learning;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a multi-layered Probabilistic Latent Semantic Analysis (PLSA) model for personalized video summarization problem based on time synchronous comments offered by multiple users. Preliminary evaluations performed on an animation series of 624 minutes long with 12212 users show that the proposed model is able to captures the relationships among the preference of each individual user and the various video events, therefore is able to generate personalized summaries of unseen videos for different users.

引用

页码：414 / 415

页数：2

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