According to the company, technical features such as applying Extreme Learning Machine algorithms, involving lexical semantics analysis, implementing word embedding techniques to capture semantic properties of words and utilizing many more proprietary methods and algorithms make Parascript’s Natural Language Processing (NLP) technology innovative and unique.
Parascript, an Intelligent Document Processing vendor, announced December 6 that it has developed an innovative Natural Language Processing (NLP) technology using an alternative machine learning approach. This approach enables Parascript to reduce deployment time and increase accuracy when extracting data from unstructured documents.
Traditional NLP technologies require time-consuming preparation and large amounts of sample data to ensure high-accuracy extraction from unstructured documents. Parascript eliminates this need through an alternative machine learning approach. It incorporates technical capabilities such as applying Extreme Learning Machine (ELM) algorithms, involving lexical semantics analysis, implementing word embedding techniques to capture semantic properties of words and utilizing many more proprietary methods and algorithms.
According to Parascript, this approach reduces the preparation time required by a human operator, as the NLP system can automatically analyze and train on a limited sample data set (3-50 samples). Thus, the proprietary technology reduces deployment time and enables higher accuracy when extracting data from unstructured documents.
Longmont, Colorado-based Parascript offers an Intelligent Document Processing (IDP) solution that automates document-centric processes in structured, semi-structured, and unstructured formats with less than 20 percent human intervention in industries such as banking, healthcare, insurance, government and others.
The full press release can be found here.
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