Automatic Document Layout Analysis through Relational Machine Learning

The current spread of digital documents raised the need of effective content-based retrieval techniques. Since manual indexing is infeasible and subjective, automatic techniques are the obvious solution. In particular, the ability of properly identifying and understanding a document’s structure is crucial, in order to focus on the most significant components only. At a geometrical level, this task is known as Layout Analysis, and thoroughly studied in the literature. On suitable descriptions of the document layout, Machine Learning techniques can be applied to automatically infer models of classes of documents and of their components. Indeed, organizing the documents on the grounds of the knowledge they contain is fundamental for being able to correctly access them according to the user’s needs.