Please wait a minute...
New Technology of Library and Information Service  2015, Vol. 31 Issue (9): 82-89    DOI: 10.11925/infotech.1003-3513.2015.09.12
Current Issue | Archive | Adv Search |
Design and Realization of Multimedia Document Structure of Internet TV
Dun Wenjie1, Sun Yigang1, Zhu Xianzhong2
1 National Library of China, Beijing 100081, China;
2 Digital Media Technology Laboratory, National Library of China, Beijing 100081, China
Export: BibTeX | EndNote (RIS)      

[Objective] Promote the construction efficiency and commonality of Internet TV multimedia resource in library and user experiences. [Context] Internet TV is one of important new media services in library. Designing suitable multimedia document structure for library is helpful to increase the efficiency of resource production and publication, and improve the commonality of resource. [Methods] According to the requirements of production, publication and exhibition of multimedia content, design an easy multimedia document structure named ZDS based on XML, and develop program tools to produce ZDS documents automatically. [Results] ZDS document can implement library multimedia materials ordered organization and packaging, and can be correctly resolved and showed on Internet TV. [Conclusions] This mode is useful to normalize construction procedures of library Internet TV resource, promote exchanging and sharing resource, and improve work efficiency.

Received: 20 March 2015      Published: 06 April 2016
:  TP391  

Cite this article:

Dun Wenjie, Sun Yigang, Zhu Xianzhong. Design and Realization of Multimedia Document Structure of Internet TV. New Technology of Library and Information Service, 2015, 31(9): 82-89.

URL:     OR

[1] Dabrowski M. Emerging Technologies for Interactive TV [C]. In: Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, Krakow, Poland. IEEE, 2013: 787-793.
[2] 陈一茜. 试述新媒体与图书馆信息服务[J]. 图书馆工作与研究, 2013(2): 45-47. (Chen Yiqian. Research on New Media and Library Information Service [J]. Library Work and Study, 2013(2): 45-47.)
[3] 李桂文. 三网融合背景下的电视图书馆建设研究[J]. 图书馆研究, 2013(1): 14-16. (Li Guiwen. Research on the Construction of the Television Library Under the Integration of the Three Networks [J]. Library Research, 2013(1): 14-16.)
[4] 汪非, 郭军, 左子端, 等. 有线数字电视图书馆的设计与实现[J]. 广播与电视技术, 2011(8): 101-106. (Wang Fei, Guo Jun, Zuo Ziduan, et al. Design and Realization of Cable DTV Library [J]. Radio & TV Broadcast Engineering, 2011(8): 101-106.)
[5] Assche S V, Hendrickx F, Oorts N, et al. Multi-Channel Publishing of Interactive Multimedia Presentations [J]. Computers & Graphics, 2004, 28(2): 193-206.
[6] Mitrovic D, Ivanovic M, Budimac Z, et al. Radigost: Interoperable Web-Based Multi-Agent Platform [J]. Journal of Systems and Software, 2014, 90: 167-178.
[7] Neto M C M, Santos C A S. StoryToCode: A New Model for Specification of Convergent Interactive Digital TV Applications [J]. Journal of the Brazilian Computer Society, 2010, 16(4): 215-227.
[8] Consumer Electronics Association (CEA). CEA-2014-B, Web-Based Protocol and Framework for Remote User Interface on UPnPTM Networks and the Internet (Web4CE) [S].
[9] Song H Y, Park J. Design of an Interoperable Middleware Architecture for Digital Data Broadcasting [J]. IEEE Transactions on Consumer Electronics, 2006, 52(4): 1433-1441.
[10] Lukac Z, Radonjic M, Mlikota B, et al. An Approach to Complex Software System Design Evaluated on the HbbTV Software Stack [C]. In: Proceedings of the 2011 IEEE International Conference on Consumer Electronics, Berlin, Germany. IEEE, 2011: 112-114.
[11] 王汉元. 置标语言以及SGML、HTML和XML的关系[J]. 情报杂志, 2005,24(3): 67-68. (Wang Hanyuan. Relationship Between Markup Language, SGML, HTML and XML [J]. Journal of Intelligence, 2005, 24(3): 67-68.)
[12] 孔令波, 唐世渭, 杨冬青, 等. XML数据的查询技术[J]. 软件学报, 2007, 18(6): 1400-1418. (Kong Lingbo, Tang Shiwei, Yang Dongqing, et al. Querying Techniques for XML Data [J]. Journal of Software, 2007, 18(6): 1400-1418.)
[13] W3C. Extensible Markup Language (XML) 1.0 (5th Edition) [EB/OL]. [2015-03-19].
[14] Phelps T E. An Evaluation of Metadata and Dublin Core Use in Web-Based Resources [J]. LIBRI: International Journal of Libraries & Information Services, 2012, 62(4): 326-335.

[1] Wang Hong, Shu Zhan, Gao Yinquan, Tian Wenhong. Analyzing Implicit Discourse Relation with Single Classifier and Multi-Task Network[J]. 数据分析与知识发现, 2021, 5(11): 80-88.
[2] Wu Yanwen, Cai Qiuting, Liu Zhi, Deng Yunze. Digital Resource Recommendation Based on Multi-Source Data and Scene Similarity Calculation[J]. 数据分析与知识发现, 2021, 5(11): 114-123.
[3] Li Zhenyu, Li Shuqing. Deep Collaborative Filtering Algorithm with Embedding Implicit Similarity Groups[J]. 数据分析与知识发现, 2021, 5(11): 124-134.
[4] Dong Miao, Su Zhongqi, Zhou Xiaobei, Lan Xue, Cui Zhigang, Cui Lei. Improving PubMedBERT for CID-Entity-Relation Classification Using Text-CNN[J]. 数据分析与知识发现, 2021, 5(11): 145-152.
[5] Yu Chuanming, Zhang Zhengang, Kong Lingge. Comparing Knowledge Graph Representation Models for Link Prediction[J]. 数据分析与知识发现, 2021, 5(11): 29-44.
[6] Ding Hao, Ai Wenhua, Hu Guangwei, Li Shuqing, Suo Wei. A Personalized Recommendation Model with Time Series Fluctuation of User Interest[J]. 数据分析与知识发现, 2021, 5(11): 45-58.
[7] Hua Bin, Wu Nuo, He Xin. Integrating Expert Reviews for Government Information Projects with Knowledge Fusion[J]. 数据分析与知识发现, 2021, 5(10): 124-136.
[8] Wang Yuan, Shi Kaize, Niu Zhendong. Position-Aware Stepwise Tagging Method for Triples Extraction of Entity-Relationship[J]. 数据分析与知识发现, 2021, 5(10): 71-80.
[9] Yang Chen, Chen Xiaohong, Wang Chuhan, Liu Tingting. Recommendation Strategy Based on Users’ Preferences for Fine-Grained Attributes[J]. 数据分析与知识发现, 2021, 5(10): 94-102.
[10] Dai Zhihong, Hao Xiaoling. Extracting Hypernym-Hyponym Relationship for Financial Market Applications[J]. 数据分析与知识发现, 2021, 5(10): 60-70.
[11] Wang Xuefeng, Ren Huichao, Liu Yuqin. Research on the Visualization Method of Drawing Technology Theme Map with Clusters [J]. 数据分析与知识发现, 0, (): 1-.
[12] Wang Yifan,Li Bo,Shi Hua,Miao Wei,Jiang Bin. Annotation Method for Extracting Entity Relationship from Ancient Chinese Works[J]. 数据分析与知识发现, 2021, 5(9): 63-74.
[13] Che Hongxin,Wang Tong,Wang Wei. Comparing Prediction Models for Prostate Cancer[J]. 数据分析与知识发现, 2021, 5(9): 107-114.
[14] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[15] Ma Jiangwei, Lv Xueqiang, You Xindong, Xiao Gang, Han Junmei. Extracting Relationship Among Military Domains with BERT and Relation Position Features[J]. 数据分析与知识发现, 2021, 5(8): 1-12.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938