Data science helps organizations communicate with stakeholders, customers, track and analyze trends, and determine if the collected data is useful. An ontology consisting of the relevant terms and connections from a specific domain streamlines the identifying of core concepts, improves classification results, and unifies data to collate critical information.
Ontology is a set of concepts and categories in a subject area or domain that possesses the properties and relations between them. It supports unstructured, semi-structured, or structured data format—thus enabling smoother data integration. It can include each aspect of the data modeling process, beginning as schemas at the initial level. Therefore, ontologies can address the vast data and improve the quality of data for training datasets used as input for machine learning training.
A domain-specific ontology, combined with Artificial Intelligence (AI)-driven tools for data analytics, can sift through the relevant data and uncover new data patterns and trends. It can help in removing word-sense disambiguation. An automated ontology can enhance machine learning and AI algorithms accuracy by providing a dynamic knowledge-base.
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