Achieve a deep, automated understanding of complex documents
Thursday, July 13 , 9:00 am PDT
Duration: 60 min.
Do you need to understand in depth the meaning of complex documents using automatic means? Go beyond the mere extraction of entities or the assignment of general categories in the analysis of financial reports, contracts, news or medical records?
The more complex a document, the more informative wealth it can bring, a wealth that escapes conventional Text Analytics. The Deep Semantic Analytics approach enables, among other possibilities, granular snippet-level coding of documents and the extraction of semantic relationships between the elements that appear in the text.
For example, these tools can receive a financial report and identify the different sections that compose it, categorizing them, and within them extract complex patterns and significant relationships between the elements that appear such as: identification and percentage of shares owned by major investors, invested companies and amount of investment, concentration of revenue in certain clients, etc.
Extracting these deep insights makes these documents much more "intelligent": more discoverable, relatable, analyzable and exploitable.
Deep Semantic Analytics tools open the door to a new generation of contextual semantic applications. Discover their possibilities in this webinar.
(Este webinar se ofrece también en español aquí.)
Thursday, July 13 2017, 9:00 am PDT
- Automatic understanding of unstructured documents: why it is not enough to extract isolated information elements.
- What Deep Semantic Analytics consists of: features and functions. Comparison with conventional text analytics.
- Where it can be applied: extracting deep insights from financial, legal, medical, etc. documents.
- Case study: Due diligence process.
- What a good solution for Deep Semantic Analytics should look like.
- MeaningCloud roadmap in Deep Semantic Analytics.
© MeaningCloud, 2017.