When engagement meets similarity

When Engagement Meets Similarity: Efficient (k, r)-Core Computation on Social Networks

In this paper, we investigate the problem of (k,r)-core which intends to find cohesive subgraphs on social networks considering both user engagement and similarity perspectives. In particular, we adopt the popular concept of k-core to guarantee the engagement of the users (vertices) in a group (subgraph) where each vertex in a (k,r)-core connects to at least k other vertices. Meanwhile, we also...

When Science Meets Religion

When Turing Meets Milner

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When Simulation Meets Antichains

We describe a new and more efficient algorithm for checking universality and language inclusion on nondeterministic finite word automata (NFA) and tree automata (TA). To the best of our knowledge, the antichain-based approach proposed by De Wulf et al. was the most efficient one so far. Our idea is to exploit a simulation relation on the states of finite automata to accelerate the antichain-bas...

When mind meets machine

into sufferers from amyotrophic lateral sclerosis (ALS) and brain-stem stroke, which enables them to move a computer cursor, albeit slowly. The device uses electrodes attached to amplifiers and FM transmitters transplanted 5 mm deep—just under the scalp—into the brain. The electrodes encourage brain tissue to grow around them, thus stabilizing them against any movement and resulting distortion ...