Emergent Mind

Measuring the Accuracy of Linked Data Indices

(1603.06068)
Published Mar 19, 2016 in cs.DB

Abstract

Being based on Web technologies, Linked Data is distributed and decentralised in its nature. Hence, for the purpose of finding relevant Linked Data on the Web, search indices play an important role. Also for avoiding network communication overhead and latency, applications rely on indices or caches over Linked Data. These indices and caches are based on local copies of the original data and, thereby, introduce redundancy. Furthermore, as changes at the original Linked Data sources are not automatically propagated to the local copies, there is a risk of having inaccurate indices and caches due to outdated information. In this paper I discuss and compare methods for measuring the accuracy of indices. I will present different measures which have been used in related work and evaluate their advantages and disadvantages from a theoretic point of view as well as from a practical point of view by analysing their behaviour on real world data in an empirical experiment.

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