Visual interfaces to the social and semantic web (VISSW 2011)

Handschuh, Siegfried; Aroyo, Lora; Thai, VinhTuan

doi:10.1145/1943403.1943508

Cited by 1 publication

(1 citation statement)

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“…This original idea has shifted from linked documents to linked data [2] nowadays. But these data are still mostly made accessible just in a human readable format (e.g., wrapped in the textual web page) which is not effective for a machine processing.…”

Section: Research Contextmentioning

confidence: 99%

Maintenance of Human and Machine Metadata over the Web Content

Rástočný

Bieliková

2012

Current Trends in Web Engineering

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Abstract. Semantics over the Web content is crucial for web information systems, e.g. for effective information exploration, navigation or search. However, current coverage of the Web by semantics is insufficient. Web information systems mostly create their own content based metadata (e.g., identified keywords) and user collaboration metadata (e.g., implicit user feedbacks) in a form of information tags -structured information with semantic relations to the tagged content. By information tags web information systems build a lightweight semantics over the Web content, in which they can store knowledge and information about the content and interconnections between information artifacts of the content. Crucial problem of information tags lies in dynamicity of the Web whose content is continually modified. This together with influence of time can lead to invalidation of information tags which are closely related to tagged content. We address this issue via maintenance approach based on automatically and semi-automatically generated rules that respect changes on the Web and time aspect. The maintenance utilizes a rule-based engine which watches changes in the tagged content, identifies dependencies among maintenance rules and builds optimal strategy of rules application. We evaluate proposed maintenance approach in two domains -programing repositories and digital libraries, which use shared information tags repository.

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Section: Research Contextmentioning

confidence: 99%