1. BioText Infrastructure Ariel Schwartz Gaurav Bhalotia 10/07/2002

2. Agenda Project Scope Timeline for Infrastructure Select Use Cases Issues

3. Project Scope An intelligent information extraction and retrieval tool for use in Biomedical and Genomics research –Enables fast and intelligent access to information needed by biological scientists –Enables easy and modular infrastructure for NLP scientists developing text-mining and text-analysis algorithms

4. Project Scope - Bio Biological Scientists need to be able to efficiently narrow down on the subset of documents showing entities and relationships between entities of interest. –Needs to be able to reach all relevant results (recall and precision) –Needs fast and easy access (indexes and keywords) –Needs some kind of pruning (ranking of search results, filtering using supplied semantics)

5. Project Scope - NLP NLP scientists who extract these relationships need to –Get a set of non-annotated text and annotated text from a lower semantic layer –Incorporate other relevant information from different sources (ontologies, thesaurus, genomic databases) together –Store a new layer of text annotations with references to the original text (including exact location) –Get biologist’s feedback on the results of the algorithm

6. For this semester Requirements Analysis Design Implementation –Simple prototype for proof of concept

7. Timeline

8. Sample Use Cases - Bio

9. Sample Use Cases - NLP

10. Conceptual Class Diagram

11. Issues Can we run NLP algorithms in batch mode (offline) and store the results in the Database? Or are the algorithms parameterized, i.e. the results depend on the query parameters that need a late binding? What are other possible use cases? Use cases that we should focus for this semester? Any other issues?