An Automatic Partitioning of Gutenberg.org Texts

Over the last 10 years, the automatic partitioning of texts has raised the interest of the community. The automatic identification of parts of texts can provide a faster and easier access to textual analysis. We introduce here an exploratory work for multi-part book identification. In an early attempt, we focus on Gutenberg.org which is one of the projects that has received the largest public support in recent years. The purpose of this article is to present a preliminary system that automatically classifies parts of texts into 35 semantic categories. An accuracy of more than 93% on the test set was achieved. We are planning to extend this effort to other repositories in the future

Using definite clause grammars to build a global system for analyzing collections of documents

International audienceCollections of documents are sets of heterogeneous documents, like a specific ancient book series, having proper structural and semantic properties linking them. A particular collection contains document images with specific physical layouts, like text pages or full-page illustrations, appearing in a specific order. Its contents, like journal articles, may be shared by several pages, not necessary following, producing strong dependencies between pages interpretations.In order to build an analysis system which can bring contextual information from the collection to the appropriate recognition modules for each page, we propose to express the structural and the semantic properties of a collection with a definite clause grammar. This is made possible by representing collections as streams of document descriptors, and by using extensions to the formalism we present here. We are then able to automatically generate a parser dedicated to a collection. Beside allowing structural variations and complex information flows, we also show that this approach enables the design of analysis stages, on a document or a set of documents. The interest of context usage is illustrated with several examples and their appropriate formalization in this framework