When meaningfully used, these new sources of information can provide significant insight and avoid unnecessary treatments, minimize adverse drug events, maximize overall safety, and eventually lead to a more effective and efficient healthcare system. It can also support the objectives of personalized medicine.
For target management, one of the most frequent use cases for expert.ai Intelligence Platform is counterparty reputational assessment, the collection and correlation of information involving a customer, supplier, business partner, etc. whenever it emerges from source.
The ideal NLU solution is one that combines the automated learning and breadth of an ML system with the human precision and industry knowledge of a rule-based one. This hybrid system requires that you can explicitly change rules based on organizational knowledge, rather than depend on the system to learn solely from examples.
Semantic technologies that have Natural Language Understanding (NLU) capability offer the advantage of a deep, contextual nderstanding of information without compromising quality in terms of precision and recall of information processed. They ensure an automatic, in-depth comprehension and offers the most promising integration and application development (both enterprise and consumer) with the most advanced predictive models.
For security and intelligence professionals tasked with protecting digital and physical assets, protecting against threats and providing timely intelligence, generating knowledge from data is essential. Analysis within the intelligence business is manifested by extracting meaning from ambiguous information, compiling comprehensive understanding from fragmentary indicators, discerning threat amidst seemingly benign activity and data, and projecting future actions and outcomes based on episodic observations of past behaviour.
Re-think how financial services research is conducted. Targeting and collecting information and looking for key words is no longer enough. Organisations must begin to deploy systems that are able to understand what information means and be able to discover how the content contained within disparate data stores are interconnected. Creation of quality research relies heavily on word context and recognizing topic relationships. It is what customers expect.
As the accurate comprehension of textual content always requires domain-specific knowledge, a knowledge graph that can be expanded upon based on the specific requirements of any use case can also offer great value.
As the information services landscape becomes more complex, your success as an information services provider hinges on your ability to deliver efficient access to the information that is most relevant to your customers and to do so while supporting their workflows.