http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Filippo Eros Pani (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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A Platform based on Kanban to Build Taxonomies and Folksonomies for DMS and CSS
Alberto Buschettu,Daniele Sanna,Giulio Concas,Filippo Eros Pani 한국정보기술융합학회 2015 JoC Vol.6 No.1
Taxonomies and folksnomies are useful tools to make documents fully accessible within a document management system. The choice of taxonomies and folksonomies is an important aspect which is often discussed without methodologies and supporting tools. Main goal of the proposed work is to define an approach based on the agile methodology Lean Kanban which allows to choose taxonomies and folksonomies. For this purpose, it has been developed a new application to support the definition, validation and implementation of taxonomies and folksonomies, according to the principle of Kanban, and to store the knowledge base which derives from it. This application aims at being a useful tool to easily implement the proposed approach and to store the metadata identified in a Document Management System or in a Cloud Storage Service.
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PCE : A Knowledge Base of Semantically Disambiguated Contents
Georgia Sanna,Antonello Angius,Giulio Concas,Dino Manca,Filippo Eros Pani 한국정보기술융합학회 2015 JoC Vol.6 No.2
With the Semantic Web people participate more actively in the building of information and take on an active role in enriching collaborative knowledge bases with user-generated contents. Moreover, new online resources have quickly gained impact on information management, such as the social bookmarking systems, which enable users to store, manage and share tagged Web content through folksonomies. These social tools allow users to associate free chosen keywords (tags) with Web content with the aim of providing an efficient navigation system through the heterogeneous amount of information available on the Web. However, the association of tags is totally arbitrary so that the use of synonyms, homonyms and new slang terms often hampers the Web information retrieval. Our project proposes the development of an innovative social bookmarking system based on a priori classification with semantic tags and structured categories extracted from online linguistic resources, which aims at disambiguating Web Content. According to this approach, each content will be described through two axes: a vertical one, concerning a hierarchical taxonomic classification and a horizontal one, dealing with a folksonomic classification. The final aim is to create a collaborative knowledge base of semantically disambiguated contents and to achieve more precise results in Web retrieval.
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