Colleagues, as most of you know, text mining is the process to derive high quality structured information from unstructured text, and its application can be very beneficial in semi-automating rapid finding of facts and relationships. Scientific abstracts are invaluable high-quality summaries for researchers. However, many facts and observations are often excluded from abstracts, appearing only within the body of the full-text article.
By combining text mining and full-text corpuses, researchers can find richer sets of results, particularly for types of information that may be underrepresented in abstracts, such as specific molecular targets.
Please feel free to view this topical webinar by Dr. George Jiang from Elsevier. As always, I welcome your feedback and questions.
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