The availability of huge amount of biomedical literature over the Web offers a big opportunity to carry out useful information about published research results. Nevertheless, these information are often enclosed in unstructured documents stressing the need to define suitable framework to support execution of analytics services and richer information discovery tasks. This work introduces a general framework to support natural language user’s query over facet-based data model. It relies on components for knowledge extraction and ontology matching to categorize input biomedical resources with respect to existing biomedical ontologies’ concepts. The framework has been instantiated implementing Fuzzy Formal Concept Analysis algorithm.
Natural Language Query Processing Framework for Biomedical Literature
DE MAIO, CARMEN;FENZA, GIUSEPPE;LOIA, Vincenzo;PARENTE, Domenico
2015-01-01
Abstract
The availability of huge amount of biomedical literature over the Web offers a big opportunity to carry out useful information about published research results. Nevertheless, these information are often enclosed in unstructured documents stressing the need to define suitable framework to support execution of analytics services and richer information discovery tasks. This work introduces a general framework to support natural language user’s query over facet-based data model. It relies on components for knowledge extraction and ontology matching to categorize input biomedical resources with respect to existing biomedical ontologies’ concepts. The framework has been instantiated implementing Fuzzy Formal Concept Analysis algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
