@Note is a Biomedical Text Mining platform that copes with major Information Retrieval and Information Extraction tasks and promotes multi-disciplinary research. In fact, it aims to provide support to three different usage roles: biologists, text miners and application developers.
The major guidelines of its development were interoperability, extensibility and user-friendly interface. The workbench is meant for both BioTM research and curation. On one hand, it supports regular curation activities, providing an intuitive Graphical User Interface (GUI) interface that does not require any knowledge about workbench or technique implementation. On the other hand, it is also meant for people with programming skills that might wish to extend the workbench capabilities.
@Note is implemented over AIBench, a JAVA framework meant to ease the development of Artificial Intelligence and Data Analysis applications. The main strengths of AIBench are its clear design and available services. Its design is problem-independent, minimum framework-related code is required in order to produce new functionalities. Moreover, it generates GUI code and enforces well-designed MVC code, supporting three main artifacts: operations, data types and views. Operations and data types are used in problem modelling while views display data in a "friendly" way.
Regarding operations, @Note sustains the general workflow of BioTM, fully covering all activities performed in manual curation. The workbench supports the retrieval, processing and annotation of documents as well as their analysis at different levels.