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Automate knowledge intensive processes through accurate Natural Language Understanding​

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Gain insight from all the information available to support strategic activities through AI-based search and discovery

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极光佛跳墙永久免费

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Why is the Knowledge Graph critical for AI?
How is Expert System's Artificial Intelligence unique?
What is the business value of Expert System’s AI?
How is cognitive search transforming knowledge discovery?
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What is the link between AI and RPA?
Why is the Knowledge Graph critical for AI?

Cogito’s Knowledge Graph is a linguistic representation of knowledge where concepts are connected to one other by semantic relationships, enabling a more accurate understanding of text. A pretrained and transparent Knowledge Graph like the one embedded in Cogito enables human-like understanding of the meaning of words in context and supports the implementation of explainable AI projects.

How is Expert System's Artificial Intelligence unique?

Expert System’s Cogito is the only Natural Language Understanding AI technology that provides a human-like understanding of the meaning of each word in a text. Cogito leverages the deepest text analysis, starting from linguistics (morphological, grammatical and syntactical analysis) to semantics, including word disambiguation and an embedded, domain-independent and pre-trained linguistic model (Knowledge Graph). This translates into the fastest, most accurate and cost effective implementation of AI in the enterprise.

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Enterprises and government organizations use Cogito to gain efficiencies by automating knowledge and document-based business processes and to make more informed decisions through the insight discovered in internal and external unstructured information sources.

How is cognitive search transforming knowledge discovery?

Cognitive search leverages NLU to increase precision, the capability to extract the correct knowledge from text, and recall, the capability to extract all the knowledge present in unstructured information. This allows an organization to more effectively use ALL the knowledge available in support of decision making processes.

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By extending the text analysis offered by NLP to understanding the meaning of words in context and of the relationships between concepts in a text, NLU provides the ability to automatically manage even complex text with high accuracy. In this way, NLU enables the application of AI to a broader and more strategic set of use cases inside the enterprise.

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AI-based text analysis allows organizations to augment and scale the capability of human-like understanding to process complex text. In this way, it expands the implementation of RPA to knowledge-intensive processes that include the management of complex information in documents.

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