As many of you already know, histoGraph is a web platform designed to help researchers to explore large multimedia archives akin to what we have here at the CVCE. The histoGraph tool has two main goals:
- To enable users to find and identify the most relevant documents for research
- To discover document connections between persons.
In the last few months our designer/developer Daniele Guido, has started the redesign and development of the tool: this screencast shows some of the new features of Histograph as well as identifying the benefits and limitations of the new design.
We can now explore the “neighborhood” of a person in terms of other co-occurring people and documents, follow the paths that connect one person to one another; or simply search for resources and pose questions related to the person or the document.
Still under development, the open source version of Histograph starts from this assumption and basically serves as recommendation system. The original database has been enriched with CVCE text documents and been transposed to a graph database in order to speed up all network related computation. Moreover, a simple and powerful text extraction chain has been added: thanks to the powerful Yago disambiguation engine, all text captions, titles and abstracts have been annotated with Named Entities in at least two languages.
Additionally, dates of both pictures and text documents have been reconciled to ISO standard; geographical places to latitude and longitude by using Geonames and Google Geocoding API; finally, person entities have been enriched with related dbpedia information. We will shortly be updating the data curation workflow to assess and validate the quality of the automatic extraction of these entities and we plan further develop our concept of expert crowdsourcing techniques.
We will use the blog to update you on progress so watch this space.