Tag Archives: Link Discovery

AKSW Colloquium, 15.02.2016, Mandolin + X-Feasible

On the 15th of February at 3 PM, Tommaso Soru will present his ongoing research titled “Mandolin: Markov Logic Networks for Discovering Links”. Later on, at 3:30 PM, our guest Adnan Akhter from HFT Stuttgart will present “X-FEASIBLE: Extended Feature-Based … Continue reading

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AKSW Colloquium, 14-12-2015, SERIMI

In the incoming AKSW Colloquium, scheduled for the 14th of December at 3 PM, Mofeed Hassan will present the paper “SERIMI: Class-Based Matching for Instance Matching Across Heterogeneous Datasets”, by Samur Araujo et al. Abstract State-of-the-art instance matching approaches do … Continue reading

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AKSW Colloquium, 14 September, 3pm, Learning Metrics for Link Discovery

In this Colloquium, Tommaso Soru will present the progress of his PhD titled “Learning Metrics for Link Discovery”. The discovery of new links is essential for the construction of the Linked Data cloud. The use of links to other URIs … Continue reading

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AKSW Colloquium, 15-06-2015, Caching for Link Discovery

Using Caching for Local Link Discovery on Large Data Sets [PDF] by Mofeed Hassan Engineering the Data Web in the Big Data era demands the development of time- and space-efficient solutions for covering the lifecycle of Linked Data. As shown … Continue reading

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LIMES Version 0.6 RC4

It has been a while but that moment has arrived again. We are happy to announce a new release of the LIMES framework. This version implements novel geo-spatial measures (e.g., geographic mean) as well as string similarity measures (jaro, jaro-winkler, … Continue reading

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Finally … Assisted Link Discovery

Hello world, We are happy to announce that LIMES has been extended with an interface that will make linking easier than ever before. The COLANUT (Complex Linking in a NUTshell) interface implements time-efficient schema matching algorithms that allow LIMES to … Continue reading

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LIMES 0.5RC1

We could not resist the pleasure of making the demo of the new release candidate of LIMES (0.5RC1) available for all. LIMES 0.5 comes fitted with a new grammar for complex metric specification and fully novel algorithms. The new version … Continue reading

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