Question answering over pattern-based user models

Comunicació presentada a la 12th International Conference on Semantic Systems celebrada a Leipzig, Alemanya, del 13-14 de setembre de 2016.In this paper we present an ontology-driven framework for natural language question analysis and answering over user models (e.g. preferences, habits and health problems of individuals) that are formally captured using ontology design patterns. Pattern-based modelling is extremely useful for capturing n-ary relations in a well-defined and axiomatised manner, but it introduces additional challenges in building NL interfaces for accessing the underlying content. This is mainly due to the encapsulation of domain semantics inside conceptual layers of abstraction (e.g. using reification or container classes) that demand flexible, context-aware approaches for query analysis and interpretation. We describe the coupling of a frame-based formalisation of natural language user utterances with a context-aware query interpretation towards question answering over pattern-based RDF knowledge bases. The proposed framework is part of a human-like socially communicative agent that acts as an intermediate between elderly migrants and care personnel, assisting the latter to solicit personal information about care recipients (e.g. medical history, care needs, preferences, routines, habits, etc.).This work has been partially supported by the H2020-645012 project /KRISTINA: A Knowledge-Based Information Agent with Social Competence and Human Interaction Capabilities"

Question answering over pattern-based user models

Comunicació presentada a la 12th International Conference on Semantic Systems celebrada a Leipzig, Alemanya, del 13-14 de setembre de 2016.In this paper we present an ontology-driven framework for natural language question analysis and answering over user models (e.g. preferences, habits and health problems of individuals) that are formally captured using ontology design patterns. Pattern-based modelling is extremely useful for capturing n-ary relations in a well-defined and axiomatised manner, but it introduces additional challenges in building NL interfaces for accessing the underlying content. This is mainly due to the encapsulation of domain semantics inside conceptual layers of abstraction (e.g. using reification or container classes) that demand flexible, context-aware approaches for query analysis and interpretation. We describe the coupling of a frame-based formalisation of natural language user utterances with a context-aware query interpretation towards question answering over pattern-based RDF knowledge bases. The proposed framework is part of a human-like socially communicative agent that acts as an intermediate between elderly migrants and care personnel, assisting the latter to solicit personal information about care recipients (e.g. medical history, care needs, preferences, routines, habits, etc.).This work has been partially supported by the H2020-645012 project /KRISTINA: A Knowledge-Based Information Agent with Social Competence and Human Interaction Capabilities"