Natural Language Processing and Natural Language Understanding allows the AIPARC platform to understand data (both unstructured and structured) with human-like understanding.
Our context discovery algorithms enable unsupervised learning with no human input, guidance or training. With our unique semiotics algorithms we are automatically able to extract and understand the correct meaning of individual words, and our deep learning capabilities recommend and discover unknown information and correlations among different data genres.
We’re applying these deep linguistic capabilities to commercial applications across digital markets to derive a new generation of behavioral models that power our ability to provide predictive and human-like response to customers to transform how business can be done anywhere.
Our context discovery platform applies semiotics to extracting and understanding the correct meaning of individual words. It interprets and communicates the meaning of data, which can be different in various data sources.
The meaning of a document is dependant on the reader’s domain knowledge and the context in which the document occurs. In order to have the correct contextual meaning, a document must be compared to all documents within the corpus to determine its meaning.
Without the use of human input, guidance or training we can automatically create order from apparent disorder at scale by discovering and extracting a meaningful hierarchical knowledge structure from unstructured content.
Leveraging the knowledge structures from our deep learning processes, we automatically extract the words and concepts that have the most importance in the context of each document. We then create summaries that provide the basis for actionable recommendations.