1,720,986 research outputs found

    Introduction to Formal representation andt he digital Humanities

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    What do linguistics, philology and even cultural studies have in common? There can be many answers for this question; certainly, however, they all have to deal with the new technologies and methods that go by the name of “Digital Humanities”. Today, all human sciences are facing new challenges both from the methodological point of view and from their very scientific contents. Accordingly, the number of research fields and approaches represented in this volume is large, reflecting the complexity of the problems of formalization, computation and digitalization of data and resources. The future of human sciences will be marked by the ever-increasing importance of formal models and computational tools, and the effective communication among the specialists of different fields is crucial for the scientific success of every single area of research. This collection of cutting-edge, high-quality papers is a fundamental step towards a better definition of the role the “Digital Humanities” will play in the next years

    ANNOTATION OF TEMPORAL INFORMATION ON HISTORICAL TEXTS: A SMALL CORPUS FOR A BIG CHALLENGE

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    This paper presents the De Gasperi corpus, a freely available linguistic resource for Italian annotated with temporal information at different levels: ie, events, temporal expressions, temporal signals and temporal relations. The De Gasperi corpus has been employed to understand how well systems built for contemporary Italian perform on historical texts and also as the starting point for the analysis of the main open issues related to the application to the history domain of an existing annotation schema, namely TimeML and its adaptation to Italian

    Introduction to Volume 2

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    Introduction to a volume on language contact in 1st millennium BCE Anatolia

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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