What DH is for: Clues in Abstracts from Literary & Linguistic Computing

I'm continuing my quest to examine current answers to the question 'What is the Digital Humanities?' In addition to the manifestos and essays in Debates in the Digital Humanities, I've been keeping my eyes peeled for implicit definitions. For example, I've highlighted a key phrase that points to an implicit definition in each of the two abstracts below:

Evidence of intertextuality: investigating Paul the Deacon's Angustae Vitae
Christopher W. Forstall, Sarah L. Jacobson, and Walter J. Scheirer
Lit Linguist Computing (2011) 26(3): 285-296 first published online May 30, 2011 doi:10.1093/llc/fqr029

Abstract: In this study, we use computational methods to evaluate and quantify philological evidence that an eighth century CE Latin poem by Paul the Deacon was influenced by the works of the classical Roman poet Catullus. We employ a hybrid feature set composed of n-gram frequencies for linguistic structures of three different kinds—words, characters, and metrical quantities. This feature set is evaluated using a one-class support vector machine approach. While all three classes of features prove to have something to say about poetic style, the character-based features prove most reliable in validating and quantifying the subjective judgments of the practicing Latin philologist. Word-based features were most useful as a secondary refining tool, while metrical data were not yet able to improve classification. As these features are developed in ongoing work, they are simultaneously being incorporated into an existing online tool for allusion detection in Latin poetry. (emphasis added)

Text encoding and ontology—enlarging an ontology by semi-automatic generated instances
Amélie Zöllner-Weber
Lit Linguist Computing (2011) 26(3): 365-370 first published online May 16, 2011 doi:10.1093/llc/fqr021

Abstract: The challenge in literary computing is (1) to model texts, to produce digital editions and (2) to model the meaning of literary phenomena which readers have in their mind when reading a text. Recently, an approach was proposed to describe and present structure and attributes of literary characters (i.e. the mental representation in a reader’s mind), to explore, and to compare different representations using an ontology. In order to expand the ontology for literary characters, users must manually extract information about characters from literary texts and, again manually, add them to the ontology. In this contribution, I present an application that supports users when working with ontologies in literary studies. Therefore, semi-automatic suggestions for including information in an ontology are generated. The challenge of my approach is to encode aspects of literary characters in a text and to fit it automatically to the ontology of literary characters. The application has been tested by using an extract of the novel ‘Melmoth the Wanderer’ (1820), written by Charles Robert Maturin. For the main character, Melmoth, 72 instances were generated and assigned successfully to the ontology. In conclusion, I think that this approach is not limited to the theme of character descriptions; it can also be adapted to other topics in literary computing and Digital Humanities. (emphasis added)

There's a clear relationship between "...validating and quantifying the subjective judgments of" [insert traditional humanities discipline here] and modeling "the meaning of literary phenomena which readers have in their mind when reading a text" (in other words, validating the subjective judgments of readers). Since I've previously stated that Tom Scheinfeldt is my new hero, I have to keep in mind that it may not be time yet for digital humanities to be answering questions. But it seems to me that validating subjective judgments may be one of the most promising avenues for digital humanities to pursue.