A framework for text processing and supporting access to collections of digitized historical newspapers


Large quantities of historical newspapers are being digitized and OCRd. We describe a framework for processing the OCRd text to identify articles and extract metadata for them. We describe the article schema and provide examples of features that facilitate automatic indexing of them. For this processing, we employ lexical semantics, structural models, and community content. Furthermore, we describe visualization and summarization techniques that can be used to present the extracted events.

Proceedings of the 12th International Conference on Human-Computer Interaction - HCII ‘07