Ricerc@Sapienza

In this paper we present CrumbTrail, an algorithm to clean large and dense knowledge graphs. CrumbTrail removes cycles, out-of-domain nodes and non-essential nodes, i.e., those that can be safely removed without breaking the knowledge graph’s connectivity. It achieves this through a bottom-up topological pruning on the basis of a set of input concepts that, for instance, a user can select in order to identify a domain of interest.

Background: Memory impairment is one of the most frequently and early detected impairment in multiple sclerosis (MS) patients. Several authors have argued that when a failure occurs in the retrieval of lexical in- formation, this might be due to a reduction of the lexical pool, related to semantic memory. Here we further investigated memory alteration in MS patients, by focusing on memory distortions (i.e., false memories) for semantically-related material.