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Intro -- Preface -- Deconstructing “DH” -- The Spirit of DH -- About This Book -- Acknowledgments -- Contents -- Authors'' Biographies -- Part I Design of Representational Systems -- Semantic Web for Cultural Heritage Valorisation -- Introduction and Motivation -- State of the Art -- Ontologies and Other Knowledge Organisation Systems -- CIDOC-CRM -- Europeana Data Model (EDM) -- Getty Vocabularies -- Projects -- Europeana -- Smartmuseum -- Museums and Linked Data -- A Cultural Heritage Data Framework: The Case of the Italian Ministry of Cultural Heritage -- Analysis of the Cultural Heritage Data Landscape -- Objectives -- Cultural-ON: The Cultural ONtologies -- Methodology -- Design Requirements -- Resulting Ontology -- The Produced Linked Open Data -- Example of Linked Open Data Aligned to Cultural-ON -- Lesson Learnt (On Methodological Principles) -- Communicating with Domain Experts -- Practices and Methods for Ontology Reuse -- Semantics of Reuse -- Sustainability of Reuse -- Interoperability and Reuse -- Direct Versus Indirect Reuse of Ontology Elements -- Minimal Reuse of Individual Entities -- Direct Reuse of Ontology Design Patterns and Alignments -- Indirect Reuse of Ontology Design Patterns and Alignments -- Concluding Remark -- Future Works -- References -- Using the Formal Representations of “Elementary Events” to Set Up Computational Models of Full “Narratives” -- Introduction -- Basic Notions About NKRL -- Linking Elementary Events -- Completive Construction -- Binding Occurrences -- NKRL Modelling of Full Narratives -- Querying/Inference Procedures -- Search Patterns -- “Transformation” Inference Rules -- “Hypothesis” Inference Rules -- Related Work -- Proposals Derived from an “Artificial Intelligence” Context -- Proposals Derived from a “Linguistics/Computational Linguistics” Context -- Conclusion -- References -- Part II Text Capture and Textual Exploration -- Parody Detection: An Annotation, Feature Construction, and Classification Approach to the Web of Parody -- Toward a Web of Derivative Works -- Context: Digital Humanities and Derivative Works -- Problem Statement: The Web of Parody -- The Need for Natural Language Features -- Background and Related Work: Detecting Appropriated Works -- Irony, Satire, and Parody Detection -- Music Video Domain -- YouTube as a Data Source -- The YouTube Social Network -- Machine Learning Task: Classification -- Methodology: Using Machine Learning to Detect Parody -- Feature Analysis and Selection -- Annotation for Supervised Learning -- Addressing the Class Imbalance Problem -- Data Acquisition and Preparation -- Data Collection and Preprocessing -- Criteria for Generation of Candidates -- Annotation -- Feature Analysis -- Feature Extraction from Text -- Experimental Results -- Statistical Validation Approach -- Results Using Different Feature Sets -- Interpretation of Results: Topic and Feature Analysis -- Summary and Future Work -- References -- Creating and Analyzing Literary Corpora -- I.