Category Archives: Announcements

Three Papers accepted at ESWC 2016

Posted on February 26, 2016 by Sandra Bartsch

We are happy to announce that three papers got accepted for presentations at the 13th Extended Semantic Web Conference (ESWC 2016), held in Heraklion, Crete, Grece. The ESWC is a important international forum for the Semantic Web / Linked … Continue reading →

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AKSW Colloquium, 22.02.2016, LDRank

Posted on February 22, 2016 by EdgardMarx

On the 22th of February at 3 PM, Edgard Marx will present a paper titled “Ranking Entities in the Age of Two Webs, An Application to Semantic Snippets”. Abstract During the last years data applications are using a big variety … Continue reading →

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AKSW Colloquium, 15.02.2016, Mandolin + X-Feasible

Posted on February 13, 2016 by TommasoSoru

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 →

Posted in Colloquium, invited talk, LinkingLOD, paper presentation | Tagged benchmarks, entity linking, Link Discovery, linked data, Papers, statistical relational learning | Comments Off

AKSW Colloquium, 01.02.2016, Co-evolution of RDF Datasets

Posted on February 1, 2016 by NatanaelArndt

At the todays colloquium, Natanael Arndt will discuss the the paper “Co-evolution of RDF Dataset” by Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour and Sören Auer (2016, available on arXiv) Link: http://arxiv.org/abs/1601.05270v1 Abstract: For many use cases it is not … Continue reading →

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Holographic Embeddings of Knowledge Graphs

Posted on February 1, 2016 by Johannes Frey

During the upcoming colloquium, Nilesh Chakraborty will give a short introduction on factorising RDF tensors and present a paper on “Holographic Embeddings of Knowledge Graphs”: Holographic Embeddings of Knowledge Graphs Authors: Maximilian Nickel, Lorenzo Rosasco, Tomaso Poggio Abstract: Learning embeddings … Continue reading →

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AKSW Colloquium, 25.01.2016, LargeRDFBench and Introduction To The Docker Ecosystem

Posted on January 25, 2016 by Ivan Ermilov

On the upcoming colloquium, Muhammad Saleem will present his paper “LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation” about the benchmarking of federated SPARQL endpoints. The other talk will be an introduction to the Docker ecosystem by Tim Ermilov. … Continue reading →

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HOBBIT project kick-off

Posted on January 22, 2016 by Sandra Bartsch

HOBBIT, a new InfAI project within the EU’s “Horizon 2020” framework program kicked-off in Luxembourg on 18 and 19 january in 2016. The main goal of the HOBBIT project (@hobbit_project on Twitter) is to benchmark linked and big data systems and assess … Continue reading →

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AKSW Colloquium, 18.01.2016, Natural Language Processing and Question Answering

Posted on January 14, 2016 by Ivan Ermilov

On the upcoming colloquium, Ivan Ermilov and Konrad Höffner, members of AKSW, will present two papers from the natural language processing (NLP) and Question Answering (QA) research areas. ClausIE: Clause-Based Open Information Extraction Authors. Del Corro, Luciano, and Rainer Gemulla. … Continue reading →

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LinkedGeoData: New RDF versions of OpenStreetMap datasets available

Posted on January 13, 2016 by Claus Stadler

The AKSW research group is happy to announce that a new LinkedGeoData maintenance release with more than 1.2 billion triples based on the OpenStreetMap planet file from 2015-11-02 is now online. Enjoy! Quick Links Project Website Downloads SPARQL Endpoint Virtual … Continue reading →

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AKSW Colloquium, 14-12-2015, SERIMI

Posted on December 13, 2015 by TommasoSoru

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 →

Posted in Colloquium, paper presentation | Tagged entity linking, heterogeneous datasets, instance matching, Link Discovery | Comments Off