A novel approach for automatic text analysis and generation for the cultural heritage domain

Knowledge is information that has been contextualised in a certain domain, to be used or applied. It represents the basic core of our Cultural Heritage and Natural Language provides us with prime versatile means of construing experience at multiple levels of organization. The natural language generation field consists in the creation of texts providing information contained in other kind of sources (numerical data, graphics, taxonomies and ontologies or even other texts), with the aim of making such texts indistinguishable, as far as possible, from those created by humans. On the other hand, the knowledge extraction, basing on text mining and text analysis tasks, as examples of the many applications born from computational linguistic, provides summarization, categorization, topics extractions from textual resources using linguistic concepts, which deal with the imprecision and ambiguity of human language. This paper presents a research activity focused on exploring and scientifically describing knowledge structure and organization involved in textual resources’ generation. Thus, a novel multidimensional model for the representation of conceptual knowledge, is proposed. Furthermore, a real case study in the Cultural Heritage domain is described to demonstrate the effectiveness and the feasibility of the proposed model and approach.