Library and Information Service >
Design and Application of Multi-dimensional Aggregation Based on Huizhou Culture Digital Resources
Received date: 2015-06-15
Revised date: 2015-06-25
Online published: 2015-07-20
[Purpose/significance] Huizhou culture is abundant and has a long history, but its digital resource presents great amount, dispersion, isomerism and multi-granularity features. Users can not accurately grasp the main line of Huizhou culture at the macro and can not clearly locate detail knowledge of Huizhou culture in the micro, so they can not find the information they need from the mass of digital resources in Huizhou culture.[Method/process] The paper integrates the advantage of linked data aggregation and classification focus aggregation in aggregation method, trying to show the full knowledge of Huizhou culture digital resources information from the macro and micro. Meanwhile we achieve the linked data aggregation from diversified sources Huizhou culture digital resource sources in the aggregation content aspect, showing the multi-dimensional aggregation based on content aspect.[Result/conclusion] We effectively show the main elements of knowledge communities and the detail of knowledge unit of Huizhou culture digital resources from the experiments. We restructure Huizhou culture digital resources from isomerism source, isomerism content and isomerism display. We realize seamless integration of library and user needs, and enhance knowledge acquisition to the user experience.
Wang Wei , Xu Xin . Design and Application of Multi-dimensional Aggregation Based on Huizhou Culture Digital Resources[J]. Library and Information Service, 2015 , 59(14) : 31 -36,58 . DOI: 10.13266/j.issn.0252-3116.2015.14.004
[1] 毕强,尹长余,滕广青,等. 数字资源聚合的理论基础及其方法体系建构[J]. 情报科学,2015(1):9-14,24.
[2] 游毅,成全. 试论基于关联数据的馆藏资源聚合模式[J]. 情报理论与实践,2013(1):109-114.
[3] Heath T, Bizer C. Linked data:Evolving the Web into a global data space[J]. Synthesis Lectures on the Semantic Web Theory & Technology, 2011,1(1):1-136.
[4] Curry E, O'Donnell J, Corry E, et al. Linking building data in the cloud:Integrating cross-domain building data using Linked Data[J]. Advanced Engineering Informatics, 2013, 27(2):206-219.
[5] 邱均平,王菲菲. 基于共现与耦合的馆藏文献资源深度聚合研究探析[J]. 中国图书馆学报,2013(3):25-33.
[6] 丁楠,潘有能. 基于关联数据的图书馆信息聚合研究[J]. 图书与情报,2011(6):50-53.
[7] Begelman G, Keller P, Smadja F. Automated tag clustering:Improving search and exploration in the tag space[C]//Proceedings of the Collaborative Web Tagging Workshop at WWW '06.Edinburgh,2006:15-33.
[8] Adrian B,Sauermann L,Roth-berghofer T.Contag:A semantic tag recommendation system[C]//Proceedings of I-SEMANTIC '07.Graz,2007:297-304.
[9] 张云中,杨萌. Tax-folk混合导航:社会化标注系统资源聚合的新模型[J]. 中国图书馆学报,2014(3):78-89.
[10] 周姗姗. 基于Folksonomy模式的数字资源多维度聚合研究[D].长春:吉林大学,2014.
[11] 伍革新. 基于关联数据的数字图书馆资源聚合与服务研究[D].武汉:华中师范大学,2013.
[12] 孙中秋. 社会化标注系统资源聚合[D].长春:吉林大学,2015.
[13] 许鑫,张悦悦. 非遗数字资源的元数据规范与应用研究[J]. 图书情报工作,2014,58(21):13-20,34.
[14] 仝召娟,许鑫,钱佳轶. 基于关联数据的非遗数字资源聚合研究[J]. 图书情报工作,2014,58(21):21-26.
[15] 夏翠娟,刘炜,赵亮,等. 关联数据发布技术及其实现——以Drupal为例[J]. 中国图书馆学报,2012(1):49-57.
[16] 沈志宏,刘筱敏,郭学兵,等. 关联数据发布流程与关键问题研究——以科技文献、科学数据发布为例[J]. 中国图书馆学报,2013(2):53-62.
[17] 徽州文化网[EB/OL].[2015-03-01]. http://www.hzwh.com/index.asp.
[18] 中国徽州文化博物馆[EB/OL].[2015-03-01].http://www.zghzbwg.com/ index.asp.
[19] 安徽师范大学自建数据库[EB/OL].[2015-03-01].http://lib1.ahnu.edu.cn/4803.
[20] 汉语分词系统[EB/OL].[2015-03-01].http://ictclas.nlpir.org.
[21] Linked Data[EB/OL]. [2015-03-01].http://www.w3.org/DesignIssues/LinkedData.html.
[22] 白海燕. 关联数据及DBpedia实例分析[J]. 现代图书情报技术,2010(3):33-39.
[23] 张冰冰. 基于领域本体的景点影视音乐推荐[D].杭州:浙江大学,2014.
/
| 〈 |
|
〉 |
