The ability to understand language and extract data in documents, manage interactions in natural language and manage unstructured information is a critical factor for competitive advantage in any industry.
Expert.ai distinguishes out of the box the correct meaning of words and expressions in context and automatically associates the attributes of more general terms that are conceptually linked to these words. This is key to successful natural language understanding. For example, it understands the terms “SUV” and “sedan,” and it automatically comprehends that these words share similar attributes that derive from both being a kind of “car.”
In addition, expert.ai identifies the relationships between concepts in a text. Both features derive from its ability to perform different levels of linguistic analysis (morphological, grammatical and sentence analysis) in conjunction with semantic analysis and word disambiguation. This human-like ability to read text and understand language is a core differentiator from other text analytics platforms because it increases accuracy, speed, and the ability to manage complex text.
Expert.ai’s knowledge graph is a representation of the real world where concepts are defined and connected to one another by semantic relationships. ‘Out of the box’ the expert.ai Knowledge Graph provides both deep and wide coverage of 400k+ English language concepts. Compared to other text analysis technologies that require cumbersome and resource-intensive initial and constant training, expert.ai leverages the embedded knowledge graph together with natural language understanding algorithms to read, comprehend and learn from any text, out-of-the-box.
Unlike other text analytics platforms, expert.ai can add domain-specific, or enterprise-specific, knowledge through both subject matter experts and proprietary machine and deep learning algorithms. Infusing real-world knowledge with disambiguation improves overall natural language model performance.