Proceedings of the First International AMICUS [antikvár]

ForewordIn cultural heritage objects, digitized or not, content Indicators occurring on higher than word level are often called motifs or their equivalent. Their recognition for document classification and retrieval is largely unresolved. Work on identifying rhetorical, narrative and persuasive elements in scientific texts has been progressing, in several, but largely unconnected tracks. The AMICUS project' (running between 2009 and 2012) set out to test a possible way to resolve these issues, starting with the identification of Proppian functions in folk tale corpora and adapting the solution to the identification of tale motifs or their functional counterparts.AMICUS has devoted its first project year to listing the corpora, tools, methods and contacts available to address these issues. The initiators of the project have identified a common need in the processing of texts from both the cultural heritage (CH) and scientific communication (SC) domains: to perform automated. large-scale higher-order text analytics, i.e., to reach an advanced level of text understanding so that structured knowledge can be extracted from unstructured text. The four research groups propose to tackle an important aspect of this complex issue by investigating how linguistic elements convey motifs in texts from tlie CM and the SC domains. Our shared working hypothesis is that the identity of higher-order content-bearing elements, i.e., textual units that are typically designated for e.g. document indexing, classification, enrichment, and the like, strongly depends on community perception.An instance of such a prominent yet little investigated content-bearing unit is a motif: an element that keeps recurring in an aitifact - e.g. in film, music, but also in folklore or scientific texts - by means of which often a narrative theme is conveyed. For example, the victory of the youngest son against all odds is a motif in folktales. In bioinformatics, the motif of a gene array study forms the mold of countless articles. In the newly developed area of web sciences, a common rhetorical motif is to refer to the threats of information overload on people. In all of these different fields, insiders are familiar with these motifs, while outsiders are not; motifs constitute a kind of high-level jargon. The modeling of motifs (and in extenso the automatic detection of motifs) is an important, and yet currently missing aspect of the analysis of CH and SC texts beyond the sentence level, on which all of the four teams are focusing their work. Interestingly, as a unit of higher-order content, the concept of motif is widespread in the CH domain (especially in literary and folkloristic genres), but not explicit in the SC domain.AMICUS aims to establish a scholarly research network with complementai-y expertise in text analytics, scholarly publishing, network studies and user studies, currently pursuing their own approaches towards the central theme of the modeling of structured knowledge (i.e. networks of knowledge) as seen against a background of different professional user communities with discipline-specific information needs. The current volume holds the papers and posters presented at our first workshop that solicited the presentation of relevant research, emerging from or pertaining to the AMICUS initiative.The P' International AMICUS Workshop is a one-day meeting that takes place on the 21 October in Vienna. The workshop is an official satellite of the Supporting the Digital Humanities conference (SDH-2010). The AMICUS workshop aims to overview methods and infrastructure related to motifs, and to facilitate community interaction and cross-fertilisation of research. We would like to express our thanks' http://amicus.uvt.nl