Linked open data offers a set of design patterns and conventions for sharing data across the semantic web. In this position paper we enumerate some key uncertainty representation i...
Temporal Constraint Satisfaction Problems allow for reasoning with events happening over time. Their expressiveness has been extended independently in two directions: to account f...
Neil Yorke-Smith, Kristen Brent Venable, Francesca...
Ontology Learning from text aims at generating domain ontologies from textual resources by applying natural language processing and machine learning techniques. It is inherent in t...
Abstract. Belief Logic Programming (BLP) is a novel form of quantitative logic programming in the presence of uncertain and inconsistent information, which was designed to be able ...
– This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic label...