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Identifier 000429205
Title ArgQL: querying argumentative dialogues using a formal, structured language
Alternative Title ArgQL: Μία τυπική και δομημένη γλώσσα υποβολής επερωτήσεων σε επιχειρηματολογικούς διαλόγους
Author Ζωγραφιστού, Δήμητρα Αντώνιος
Thesis advisor Πλεξουσάκης, Δημήτριος
Reviewer Φλουρής, Γιώργος
Bikakis, Antonis
Antoniou, Grigoris
Reed, Chris
Hunter, Anthony
Zablith, Fouad
Abstract In light of the rapid evolution of social media that we experience over the past decade, and their establishment as one of the main means of communication and dialogical exchange, the problem of extracting meaningful information from data residing in human dialogues is now more crucial than ever. Until recently, the challenges associated with this problem were being addressed as an application domain for the computational models of fields like the Semantic Web, Information Retrieval, Data Mining etc. However, there are some information requirements when searching in dialogues which are quite specific and common for all types of dialogues, regardless of their context or goal, e.g. concerning the structure of the different opinions and the correlations among them, which could stand as an autonomous area to study. Isolating those requirements and bringing them together in the specification of a formal language, designed exclusively for this purpose, is a research direction which has been given less attention. Incited by this deficiency, in this thesis we introduce ArgQL (Argumentation Query Language), a high-level declarative language for querying dialogical data. ArgQL provides a simple and dialogue-related terminology to write queries in the domain, which in existing query languages would be quite difficult to express. The theory that founds the data model adopts some of the most prevailing semantics in the area of Computational Argumentation. As a result, the target data consist of graphs of interconnected, structured arguments and ArgQL allows for the navigation across such graphs. We present the formal specification of the language, including the definition of its main constructs, the concrete syntax, as well as the semantics that determine the evaluation of those constructs against the data model. Subsequently, we propose a methodology to translate ArgQL into other languages and in particular we show the case of RDF and its associated query language, SPARQL. To this end, we define an RDF scheme based on the AIF conceptualization and we formalize the mappings between this and our data model. We then build the process of query translation, as a set of rules that define the correspondence between the different ArgQL constructs and the respective SPARQL graph patterns. The soundness and completeness of the process is verified by proving the equivalence between the matching data for each of these two languages, with respect to their formal semantics. Although correct, the conformation to the precise definition of the translation rules results to non-optimal queries. Therefore, on top of this methodology, we propose some optimization, that succeeds shorter and by extension more efficient queries. We also give prominence to the practical side of ArgQL and we implement the language, allowing for its execution on real data-sets. Thus, one of the outcomes of this work was an online query endpoint, where someone can test his own queries. Finally, we conduct an experimental study to evaluate the query performance under different execution parameters.
Language English
Subject AIF
Computational Argumentation
Graph Query Languages
Semantic Web
Γλώσσες επερωτήσεων σε γράφους
Σημασιολογικός ιστός
Υπολογιστική επιχειρηματολογία
Issue date 2020-03-27
Collection   Faculty/Department--Faculty of Sciences and Engineering--Department of Computer Science--Doctoral theses
  Type of Work--Doctoral theses
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