activity
20152021
most citedTowards Efficient Evolving Multi-Context Systems (Preliminary Report)

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2021

Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL

Ricardo Ferreira, Carolina Lopes, Ricardo Gonçalves +3

The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly. Processing all this data in real-time, while…

cs.AI2021

Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks

João Ferreira, Diogo Lavado, Ricardo Gonçalves +3

With the constant increase of available data in various domains, such as the Internet of Things, Social Networks or Smart Cities, it has become fundamental that agents are able to…

cs.AI2019

A Syntactic Operator for Forgetting that Satisfies Strong Persistence

Matti Berthold, Ricardo Gonçalves, Matthias Knorr +1

Whereas the operation of forgetting has recently seen a considerable amount of attention in the context of Answer Set Programming (ASP), most of it has focused on theoretical aspec…

cs.AI20152 cited

Towards Efficient Evolving Multi-Context Systems (Preliminary Report)

Ricardo Gonçalves, Matthias Knorr, João Leite

Managed Multi-Context Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. Recently, evolving Multi-Context Systems (eM…

cs.AI2015

On Minimal Change in Evolving Multi-Context Systems (Preliminary Report)

Ricardo Gonçalves, Matthias Knorr, João Leite

Managed Multi-Context Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms. However, mMCSs are essentially static as the…