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Large Knowledge Collider


The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced "lark"), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web. This will be achieved by:  

  • Enriching the current logic-based Semantic Web reasoning methods with methods from information retrieval, machine learning, information theory, databases, and probabilistic reasoning.
  • Employing cognitively inspired approaches and techniques such as spreading activation, focus of attention, reinforcement, habituation, relevance reasoning, and bounded rationality.
  • Building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via "computing at home".

  The consortium is an interdisciplinary team of engineers and researchers in Computing Science, Web Science and Cognitive Science, well qualified to realize this ambitious vision. The Large Knowledge Collider will be an open architecture. Researchers and practitioners from outside the consortium will be encouraged to develop and plug in their own components to drive parts of the system. This will make the Large Knowledge Collider a generic platform, and not just a single reasoning engine. The success of the Large Knowledge Collider will be demonstrated in three end-user case studies. The first one is from the telecommunication sector. It aims at real-time aggregation and analysis of location data obtained from mobile phones carried by the population of a city, in order to regulate city infrastructure functions such as public transport and to provide context-sensitive navigation information. The other two case studies are in the life-sciences domain, related respectively to drug discovery and carcinogenesis research. Both will demonstrate that the capabilities of the Large Knowledge Collider go well beyond what is possible with current Semantic Web infrastructure.

Historical Project: 
No Historical Project