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Challenges for Consuming and Mining Linked Data

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Challenges for Consuming and Mining Linked Data

Kolloquium Angewandte Informatik

Significant bottlenecks and technical limitations that prevent Linked Data from realizing its maximum potential remain still open despite of the early success of the Linked Open Data initiatives. In this talk, we focus on challenges for data mining and query processing against different web-based sources. In the first part of the talk, we present the problem of predicting interactions between linked entities, and describe an unsupervised method that predicts potential new interactions from communities of similar drugs and targets that highly interact; behavior of the proposed link prediction technique is compared with respect to existing machine learning approaches. In the second part, we discuss query rewriting, source selection, and query execution in the context of Linked Data. Behavior and limitations of the proposed query processing techniques are framed in the context of Web-querying infrastructures such as federation of SPARQL endpoints. We finalize the presentation with an outlook to open issues that have to be achieved to maximize the power of updatable data sources, e.g., open and time-dependent sources, and Web APIs.

(Prof. Dr. Maria-Ester Vidal)

Start: 10. Juni 2014 um 14:00
Ende: 10. Juni 2014 um 15:00

Im Gebäude 11.40, Raum: 253

Veranstaltung vormerken: (iCal)

Veranstalter: Forschungsgruppe(n) Wissensmanagement