A Lightweight Linked Data Reasoner Using Jena and Axis2

Hsu, I-Ching; Lyu, Sin-Fong

doi:10.1007/978-3-030-22999-3_34

Cited by 1 publication

(1 citation statement)

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“…LOD contains a structured information resource that is written in resource description framework (RDF)‐based format to facilitate machine readability. It can facilitate inferring new data resources at runtime through RDF‐based links and then provide more complete answers as new data resources appear on the Internet 24 . A well‐known example of a LOD set is DBpedia, one of the most popular and widely used data sets on the semantic web.…”

Section: Related Workmentioning

confidence: 99%

Integrated machine learning with semantic web for open government data recommendation based on cloud computing

Hsu

Lin

2020

Softw Pract Exp

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Summary Open government data (OGD) is a type of trusted information that can be used to verify the correctness of information on social platforms. Finding interesting OGD to serve personalized needs to facilitate the development of social platforms is a challenging research topic. This study explores how to link the Taiwanese government's open data platform with Facebook and how to recommend related OGD. First, an integrated machine learning with semantic web into cloud computing framework is defined. Next, the linked data query platform (LDQP) is developed to validate its feasibility. The LDQP provides a graphical approach for personal query and links with related Facebook fan pages. LDQP automatically finds highly relevant OGD based on recent topics that users are following on Facebook when users login to Facebook via the LDQP. In this way, the LDQP query result can be dynamically adjusted and graphically displayed according to user's Facebook operations.

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Section: Related Workmentioning

confidence: 99%