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Similaire à Roeder rocky 2011_46
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Roeder rocky 2011_46
- 1. A Distributed Framework for Computation on the Results of Large Scale NLP Christophe Roeder, William A. Baumgartner Jr., Kevin Livingston, Lawrence E. Hunter (University of Colorado Anschutz Medial Campus) Chris.Roeder@ucdenver.edu http://compbio.ucdenver.edu
- 2. Motivation • A vast amount of information is available in journal articles • Journal articles are unstructured text • Many applications require structured knowledge – Curated ontologies (Gene Ontology) – Databases (UniProt, EntrezGene) • Challenge: extract structured knowledge from unstructured text and integrate with existing knowledge…at massive scale
- 3. Architecture Journal RDF Scaled NLP Pipeline Articles(u Document nstructured) s(structured) Queries Sesam Knowledge e/Hado Base(Ontologi op es, Databases) Knowledg Applications Applications (Visualization e Distilled Applications (Visualization , (Visualization NLP,…) , NLP,…) Output , NLP,…) (structured) Structured Information
- 4. Example Application • Concept annotation trends over time Insuli n NOS1 http://tinyurl.com/bio-trends
- 5. Summary • NLP pipelines extract structured annotations • Our framework provides massively parallel access to these structured document annotations • Structured representation is integrated with knowledge base • Affords parallelization when possible, and access to knowledge base when necessary • Provides integration of unstructured document text with structured knowledge for enabling applications such as: – Visualization (BioJigsaw, Hanalyzer,…) – Natural Language Understanding (OpenDMAP) – Leveraging text data for validation and evaluation of other methods
- 6. Thank You / Questions • http://tinyurl.com/bio-trends • Co-authors – William A. Baumgartner Jr. for data generation – Kevin Livingston for RDF and Clojure help • Grants and PIs – Lawrence E Hunter, UCDenver SOM • NIH 2R01LM009254-04, NIH 2R01LM008111-04A1, NIH 5R01GM083649-02 – Karin Verspoor, UCDenver SOM • NIH R01 LM010120-01 – Gully Burns, ISI • NSF 0849977
Notes de l'éditeur
- Plug KabobPlug Open Access, Mention Elsevier collections, size
- Mention UIMA Distringuish NER from normalization, and how that ID ties it into the KBPutting High Precision Enttiytrecog to work at large scaleInduction, abductionGet around noise issues by using a LOT of dataPrecision and recal require scaleMight learn something, if said often enoughCorrleations between proteins, coorrenceppiCoorrence with other ontology terms or other extracted terms or biological processes
- No excuses, don’t trivialize, but emphasize its value as a demoBuilt in about a week, computation over PMC OA in 2 hours on a very modest cluster (40 cores)(inefficiencies exist as well) lot of data, runs qucilyDemonstrates that the framework can be used quickly and worksSame technology can be used
- On that last point, think of coorelatoins and stuff.** who knows what we’ll think of with the possibilities this opens up