Doctoral Consortium – Paper 14

Retrieval of the most relevant facts from data streams joined with slowly evolving dataset published on the Web of Data

Shima Zahmatkesh

Doctoral Consortium

clock_eventOctober 18, 2017, 14:00.
house TC.3.07
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Abstract

Finding the most relevant facts among dynamic and heterogeneous data published on the Web of Data is getting a growing attention in recent years. RDF Stream Processing (RSP) engines offer a baseline solution to integrate and process streaming data with data distributed on the Web. Unfortunately, the time to access and fetch the distributed data can be so high to put the RSP engine at risk of losing reactiveness, especially when the distributed data is slowly evolving. State of the art work addressed this problem by keeping the replica of background data and offering maintenance process to ...