Discovering Novelty Patterns from the Ancient Christian Inscriptions of Rome

Author:

Pio Gianvito1,Fumarola Fabio1,Felle Antonio E.1,Malerba Donato1,Ceci Michelangelo1

Affiliation:

1. University of Bari Aldo Moro

Abstract

Studying Greek and Latin cultural heritage has always been considered essential to the understanding of important aspects of the roots of current European societies. However, only a small fraction of the total production of texts from ancient Greece and Rome has survived up to the present, leaving many gaps in the historiographic records. Epigraphy, which is the study of inscriptions (epigraphs), helps to fill these gaps. In particular, the goal of epigraphy is to clarify the meanings of epigraphs; to classify their uses according to their dating and cultural contexts; and to study aspects of the writing, the writers, and their “consumers.” Although several research projects have recently been promoted for digitally storing and retrieving data and metadata about epigraphs, there has actually been no attempt to apply data mining technologies to discover previously unknown cultural aspects. In this context, we propose to exploit the temporal dimension associated with epigraphs (dating) by applying a data mining method for novelty detection. The main goal is to discover relational novelty patterns—that is, patterns expressed as logical clauses describing significant variations (in frequency) over the different epochs, in terms of relevant features such as language, writing style, and material. As a case study, we considered the set of Inscriptiones Christianae Vrbis Romae stored in Epigraphic Database Bari, an epigraphic repository. Some patterns discovered by the data mining method were easily deciphered by experts since they captured relevant cultural changes, whereas others disclosed unexpected variations, which might be used to formulate new questions, thus expanding the research opportunities in the field of epigraphy.

Funder

Seventh Framework Programme

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Information Systems,Conservation

Reference29 articles.

1. Mining and Filtering Multi-level Spatial Association Rules with ARES

2. Mario Borillo. 1984. Stratégies de mise à l'épreuve de conjectures historiques. In Informatique pour les sciences de l'homme. Bruxelles. Mario Borillo. 1984. Stratégies de mise à l'épreuve de conjectures historiques. In Informatique pour les sciences de l'homme. Bruxelles.

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