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Qint is a cloud-based data processing platform that enables users to gather meaningful insights from unstructured text. It allows you to merge the results of unstructured, text-based analytics with structured data to create a searchable index for data mining and predictive analytics.
Qint recognizes correlations using machine learning algorithms. New algorithm models can be trained to identify custom entities and word usage specific to your domain.
The dashboard in Qint presents information through intuitive graphs and charts. You can easily drill down to specifics or filter reports as needed.
Qint offers the option to export crawled or analyzed documents as well as search results in multiple file formats, including CSV and XML.
Qint executes the following steps to identify mentions and relations in unstructured text.
The platform is configured to collect structured and unstructured content from documents, emails, databases, websites, and other data repositories. Data can be fed into the platform manually or at scheduled intervals using cron jobs. The platform offers a set of tools to import data from external locations and also a permanent storage for data.
Qint data processing engine can analyze the unstructured data in its storage and identify unique user-defined relations between entities based on the custom data models defined.
Qint provides easy-to-use user interface tools for annotating unstructured domain literature. The annotations are used to create a custom machine-learning model that understands the lingo of the domain. The model, trained on a set of domain-specific source documents, is used to find entities, relations, and coreferences in new documents.
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