Text mining is used in a variety of ways to identify and extract information from documents.  Using Natural Language Processing (NLP) with text mining, data may be extracted to reveal facts and relationships that provide directly relevant information to address specific questions. This presentation will explore various examples to demonstrate increasing value from text mining as different NLP techniques are applied.  The talk will provide insight into ways chemical data from a variety of sources such as patents and full-text journal articles can be text mined.  Further, an innovative federated approach will be presented to mine multiple data sources and get back comprehensive results.<br/>

From documents to knowledge

253rd National Meeting (2017)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.