Icertis. has been granted a patent for a machine learning engine that processes contract documents to predict attribute values. The engine selects training and validation documents, evaluates models based on accuracy, and generates confirmed models to enhance prediction efficiency and accuracy, incorporating geolocation and localization features. GlobalData’s report on Icertis gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Icertis, Speech recognition techniques was a key innovation area identified from patents. Icertis's grant share as of June 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning for managing and predicting contract document attributes
The patent US12020130B2 outlines a method and system for managing contract documents over a network, utilizing advanced processing techniques. The method involves instantiating an engine that performs several actions, including the selection of training and validation contract documents from a larger pool. It employs both semantic and textual evaluators to identify attributes related to localization features, such as time zones, languages, and currencies. Additionally, the system incorporates geolocation technology to ascertain the physical location relevant to the contract documents, which aids in validating categories of contract clauses. The process further includes determining candidate models based on training accuracy scores and generating confirmed models that enhance the efficiency and accuracy of predicting attribute values for selected contract documents.
Moreover, the patent details additional functionalities, such as training multiple models to predict attribute values and identifying candidate attributes within the contract documents. The system is designed to detect outlier attributes and predict unknown values for working documents using high-ranked candidate models. The architecture comprises a network computer with memory and processors that execute the necessary instructions, as well as a client computer that provides access to the contract documents. This comprehensive approach aims to streamline contract management processes, ensuring that the predictions made are both resource-efficient and accurate, thereby improving overall operational effectiveness in handling contract documentation.
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