Towards a Decision Support System for Text Intepretation
Authors: Alessia Bellusci, Andrea Bellandi, Giulia Benotto, Amedeo Cappelli, Emiliano Giovannetti, Simone Marchi (CNR-ILC, 2014)
Topic: Latin Resources

Abstract
This article illustrates the first steps towards the implementation of a De-cision Support System aimed to recreate a research environment for scholars and pro-vide them with computational tools to as-sist in the processing and interpretation of texts. While outlining the general charac-teristics of the system, the paper presen-ts a minimal set of user requirements and provides a possible use case on Dante’s Inferno.

Introduction
A text represents a multifaceted object, resulting from the intersection of different expressive layers (graphemic, phonetic, syntactic, lexico-semantic, ontological, etc.). A text is always created by a writer with a specific attempt to outline a certain subject in a particular way. Even when it is not a literary creation, a given text follows its wri-ter’s specific intention and is written in a distinct form. The text creator’s intention is not always self-evident and, even when it is, a written piece might convey very different meanings proportio-nally to the various readers analysing it. Texts can be seen, in fact, as communication media between writers and readers. Regardless of the epistemolo-gical theory about where meaning emerges in the reader-text relationship (Objectivism, Constructi-vism, Subjectivism), a text needs a reader as much as a writer to be expressive (Chandler, 1995). The reader goes beyond the explicit information given in the text, by making certain inferences and eva-luations, according to his/her background, expe-rience, knowledge and purpose. Therefore, inter-pretation depends on both the nature of the given text and the reader/interpreter; it can be understood as the goal, the process and the outcome of the analytic activity conducted by a certain reader on a given text under specific circumstances. Interpretation corresponds to the different– virtually infinite– mental frameworks and cognitive mechanisms activated in a certain reader/interpreter when examining a given text. The nature of the interpretation of a given text can be philological, historical, psychological, etc.; a psychological interpretation can be Freudian, Jungian, etc... Furthermore, the different categories of literary criticism and the various interpretative approaches might be very much blurred and intertwined, i.e. an historical interpretation might involve philological, anthropological, political and religious analyses. While scholars are generally aware of their mental process of selection and categorization when reading/interpreting a text and, thus, can re-adjust their interpretative approach while they operate, an automatic system has often proved unf it for qualitative analysis due to the complexity of text meaning and text interpretation (Harnad, 1990). Nevertheless, a few semi-automatic systems for qualitative interpretation have been proposed in the last decades. The most outstanding of them is ATLAS.ti, a commercial system for qualitative analysis of unstructured data, which has been applied in the early nineties to text interpretation (Muhr, 1991). ATLAS.ti, however, appears too general to respond to the articulated needs of a scholar studying a text, lacking of advanced text analysis tools and automatic knowledge extraction features. The University of Southampton and Birkbeck University are currently working on a commercial project, SAMTLA1, aimed to create a language-agnostic research environment for studying textual corpora with the aid of computational technologies. In the past, concerning the interpretation of literary texts, the introduction of text annotation approaches and the adoption of high-level markup languages allowed to go beyond the typical use of concordances (DeVuyst, 1990; Sutherland, 1990; Sperberg-Mc Queen and Burnard, 1994). In this context, several works have been proposed for the study of Dante’s Commedia. One of the first works involved the definition of a meta representation of the text of the Inferno and the construction of an ontology formalizing a portion of Dante’s Commedia’s world (Cappelli et al., 2002). Data mining procedures able to conceptually query the aforementioned resources have also been implemented (Baglioni et al., 2004). Among the other works on Dante we cite The World of Dante (Parker, 2001), Digital Dante of the Columbia University (LeLoup and Ponterio, 2006) and the Princeton Dante Project (Hollander, 2013). A “multidimensional” social network of characters, places and events of Dante’s Inferno have been constructed to make evident the innermost structure of the text (Cappelli et al., 2011) by leveraging on the expressive power of graph representations of data (Newman, 2003; Newmanetal., 2006; Easley and Kleinberg, 2010; Meirelles, 2013). A touch table approach to Dante’s Inferno, based on the same social network representation, has been also implemented (Bordin et al., 2013). More recently, a semantic network of Dante’s works has been developed alongside a RDF representation of the knowledge embedded in them (Tavoni et al., 2014). Other works involving text interpretation and graph representations have been carried out on other literary texts, such as Alice in Wonderland (Agarwal et al., 2012) and Promessi Sposi (Bolioli et al., 2013). As discussed by semiologists, linguists and literary scholars (Eco, 1979; Todorov, 1973; Segre, 1985; Roque, 2012) the interpretation of a text may require a complex structuring and interrelation of the information belonging to its different expressive layers. The Decision Support System (DSS) we here introduce aims to assist scholars in their research projects, by providing them with semi-automatic tools specifically developed to support the interpretation of texts at different and combined layers. Wechose to start from the analysis of literary texts to be able to face the most challenging aspects related to text interpretation. This work is the third of a series describing the progressive development of the general approach: for the others refer to (Bellandi et al., 2013; Bellandi et al., 2014). In what follows, we describe the general characteristics of the DSS we plan to develop accompanied by aminimal set of user requirements (2.), we present a possible scenario, in which the system can be applied (3.), and we provide some conclusive notes (4.).

Conclusion
In this work, we presented our vision of a Decision Support System for the analysis and interpretation of texts. In addition to outlining the general characteristics of the system, we illustrated a case study on Dante’s Inferno showing how the study of a text can involve elements belonging to three different layers (ontological, dialogical and terminological) thus allowing to take into account, in an innovative way, both textual and contextual elements. The next steps will consist in the extension of the user requirements and the design of the main components of the system. We plan to start with the basic features allowing a user to create a project and upload documents and then provide the minimal text processing tools necessary for the definition and management of (at least) the graphemic layer.