CrowdHeritage: Improving the quality of Cultural Heritage through crowdsourcing methods

被引:1
作者
Ralli, Maria [1 ]
Bekiaris, Spyros [1 ]
Kaldeli, Eirini [1 ]
Menis-Mastromichalakis, Orfeas [1 ]
Sofou, Natasa [1 ]
Tzouvaras, Vassilis [1 ]
Stamou, Giorgos [1 ]
机构
[1] Natl Tech Univ Athens, Sch Elect & Comp Engn, Artificial Intelligence & Learning Syst Lab, Athens, Greece
来源
2020 15TH INTERNATIONAL WORKSHOP ON SEMANTIC AND SOCIAL MEDIA ADAPTATION AND PERSONALIZATION (SMAP 2020) | 2020年
基金
欧盟地平线“2020”;
关键词
crowdsourcing; automatic enrichment; user validation; annotations model;
D O I
10.1109/smap49528.2020.9248463
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The lack of granular and rich descriptive metadata highly affects the discoverability and usability of the digital content stored in museums, libraries and archives, aggregated and served through Europeana, thus often frustrating the user experience offered by these institutions' portals. In this context, metadata enrichment services through automated analysis and feature extraction along with crowdsourcing annotation services can offer a great opportunity for improving the metadata quality of digital cultural content in a scalable way, while at the same time engaging different user communities and raising awareness about cultural heritage assets. Such an effort is Crowdheritage, an open crowdsourcing platform that aims to employ machine and human intelligence in order to improve the digital cultural content metadata quality.
引用
收藏
页码:168 / 173
页数:6
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