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Integrated health services are characterized by a high degree of collaboration and communication among health professionals, as well as a merge of political, administrative, and technical actions, which can allow the sharing of information among healthcare team members (physicians, nurses, managers, and other stakeholders) related to patient care, and access to hospital infrastructure and technology, within a patient-centered approach. In this paper, we propose a technological solution based on software agents, which allows supporting the management of collaborative processes in environments of dynamic collaborative networks. We present a methodology for coordinating healthcare services through collaborative processes to enable organizations providing integrated care services and continuous process improvements. This methodology includes methods based on Model-Driven Development, which enable the generation of executable process models and the code of the process-oriented agents, derived from conceptual models of collaborative processes. The methodology and methods are implemented and automated by software agents that enable the generation of the technological solution, at run-time on the platform. Furthermore, we propose an agent-based platform that enables organizations to negotiate collaboration agreements in electronic format to establish collaborative networks, as well as a definition of the collaborative processes to be executed. In this way, the proposed agent-based platform allows collaborations among heterogeneous and autonomous healthcare organizations focusing on the process-oriented integration, enabling us to provide integrated healthcare services. [ABSTRACT FROM PUBLISHER]

Domain ontologies facilitate the organization, sharing, and reuse of domain knowledge. The construction of ontologies from text deals with the extraction of concepts and relations from text collection. A huge challenge is the learning of more expressive ontologies which includes relations such as disjointness or equivalence between classes. In our work, we exploit a text collection written in English with occurrence of named entities giving information about individuals in an specific domain knowledge for generating axioms. The co-ocurrence in texts of named entities is exploited to establish axiomatic relations between classes such as subClassOf, disjointWith, and equivalentClass; as well as between individuals as sameIndividualAs and differentFrom by using the instanceOf relation. For this purpose, a Named Entity Recognition tool was used for the identification of instanceOf relation, the linguistic context where the classes co-occur was extracted for the identification of axioms. The experiments were made on a text collection about the tourist domain. The results show that named entities provide good evidence for the identification of axiomatic relations. [ABSTRACT FROM PUBLISHER]

Two novel techniques based on term expansion for domain-specific Word Sense Disambiguation are presented in this paper. A list of terms correlated with the ambiguous word is obtained by means of correlation methods such as Pointwise Mutual Information and Chi-square. The list of correlated terms is used for expanding the context in which an ambiguous word occurs, thus leading to a better number of terms which may be further used for determining the correct sense of the target ambiguous word. The proposed method has been tested in domain-specific corpora (Finance and Sports) and in one balanced corpus, the British National Corpus (BNC). The obtained results for domain-specific corpora are competitive (Finance) and ever better (Sports and BNC) than those reported in previous works. [ABSTRACT FROM PUBLISHER]