We introduce our solution developed for data privacy, and specifically for cognitive security that can be enforced and guaranteed using blockchain technology in SAAL (Smart Ambient Assisted Living) environments. Personal clinical and demographic information segments to various levels that assures that it can only be rebuilt at the interested and authorized parties and no profiling can be extracted from the blockchain itself. Using our proposal the access to a patient's clinical process resists tampering and ransomware attacks that have recently plagued the HIS (Hospital Information Systems) in various countries. The core of the blockchain model assures non-repudiation possible by any of the involved information producers thus maintaining ledger fidelity of the enclosed historical process information. One important side effect of this data infrastructure is that it can be accessed in open form, for research purposes for instance, since no individual re-identification or group profiling is possible by any means.

Question Answering systems that resort to the Semantic Web as a knowledge base can go well beyond the usual matching words in documents and, preferably, find a precise answer, without requiring user help to interpret the documents returned. In this paper, the authors introduce a Dialogue Manager that, through the analysis of the question and the type of expected answer, provides accurate answers to the questions posed in Natural Language. The Dialogue Manager not only represents the semantics of the questions, but also represents the structure of the discourse, including the user intentions and the questions context, adding the ability to deal with multiple answers and providing justified answers. The authors' system performance is evaluated by comparing with similar question answering systems. Although the test suite is slight dimension, the results obtained are very promising.

The Ontology for General Medical Science (OGMS) complemented with the Computer-Based Patient Record Ontology (CPR)is based on several upper ontologies which may have formal ontological relations according to the OBO Foundry principles. These ontologies accordant to the underlying Ontological Realism render a structure with reasoning capabilities that reach further than those possible with logical formalisms alone. We propose to extend carefully the OGMS taking into account the diverse ontological relations found in the recently proposed Basic Formal Ontology V2, FMA and SNOMED-CT as foundational ontologies in order to extract axioms for ontology enrichment from natural language text. With these cautions in mind, using careful instantiation we improve largely the reasoning capabilities over the resulting OWL knowledge base. Most of the clinical practice knowledge is currently recorded in SOAP text format. We extend the OGMS with the CPR structure into an Ontology for General Clinical Practice (OGCP) for the generation of adequate ontologically rich axioms from the SOAP text segments.)

We present a collaborative dialogue framework for web information retrieval systems. The dialogue manager, whose main role is to help users in their documents searches, infers the user and system intentions, represents the interaction context and behaves as an intelligent interface between the user and the information retrieval system. The knowledge used by the dialogue manager in the inference and fulfilment of user and system intentions is mainly obtained trough the intelligent clustering of the documents in the database. The system also uses a knowledge base with some rules modelling domain knowledge on the documents subject (in our application, juridical knowledge). A detailed example in the law field is presented. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.