Health information becomes importantly valuable for protecting public health in the current
coronavirus situation. Knowledge-based information systems can play a crucial role in …

In this paper we investigate the relationships between a multipreferential semantics for
defeasible reasoning in knowledge representation and a deep neural network model …

Logs record system events and status, which help developers and system administrators
diagnose run time errors, monitor running status and mine operation patterns [13, 23] …

Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard.
We explain how knowledge graph embeddings can be used to approximate probabilistic …

With recent viruses across the world affecting millions and millions of people, the self-
healthcare information systems show an important role in helping individuals to understand …

We investigate ontology-based query answering for data that are both temporal and
probabilistic, which might occur in contexts such as stream reasoning or situation …

Professional profiles are unstructured documents where the knowledge and experience of
the editor predominate, presenting inconsistencies and ambiguities in terms of the …

The coalgebraic µ-calculus provides a generic semantic framework for fixpoint logics over
systems whose branching type goes beyond the standard relational setup, eg probabilistic …

Every scientific or intellectual movement rests on central premises and assumptions that
shape its philosophy. The purpose of this study is to review a brief account of the main …

Ontologies and vector space embeddings are among the most popular frameworks for
encoding conceptual knowledge. Ontologies excel at capturing the logical dependencies …