Interactive Text Analysis and Information Extraction

A lot of work that has been done in the text mining field concerns the extraction of useful information from the full-text of publications. Such information may be links to projects, acknowledgements to communities, citations to software entities or datasets and more. Each category of entities, according to its special characteristics, requires different approaches. Thus it is not possible to build a generic mining platform that could text mine various publications to extract such info. Most of the time, a field expert is needed to supervise the mining procedure, decide the mining rules with the developer, and finally validate the results. This is an iterative procedure that requires a lot of communication among the experts and the developers, and thus is very time-consuming. In this paper, we present an interactive mining platform. Its purpose is to allow the experts to define the mining procedure, set/update the rules, validate the results, while the actual text mining code is produced automatically. This significantly reduces the communication among the developers and the experts and moreover allows the experts to experiment themselves using a user-friendly graphical interface.