Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis

In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.

► We model an ontology through Fuzzy Formal Concept Analysis (FFCA) theory.
► FFCA provides a hierarchy of extracted knowledge through concepts.
► The ontology-based retrieval model accomplishes the visualization, navigation and classification of the knowledge.
► 4-Steps mapping translates the concept lattice structure into an OWL ontology.
► A graphical interface provides a multi-facets view of the built ontology.