How You Can Use AI to Sort Unstructured Data

How You Can Use AI to Sort Unstructured Data

AI has several use cases, and one of them is the recognition pattern to sort unstructured data. There are six other patterns that you can use for data. They are hyper-personalization, autonomous systems, predictive analytics and decision support, conversational/human interactions, patterns and anomalies, and goal-driven systems. In this article at Analytics Insight, Preetipadma shares how to use AI to sort unstructured data.

Arranging Unstructured Data

Humans can figure out structured data using the query, stack, and informatics systems. For the unstructured data, AI can identify the patterns that human eyes miss. With the help of the training data you fed into them, the machines can understand common keywords and classes. They then leverage the labels to classify the data. Here are the AI use cases for unstructured data:


Machine learning systems can use recognition patterns to analyze video streaming in real-time. Track vehicles involved in illegal activities. You can also utilize the design to check if people follow social distancing or wear masks in public areas.


You can detect bone cracks, obstructions, aneurysms, cancerous shapes, tuberculosis, and even COVID-19 viruses with patterns.

Ecommerce Cataloguing

Thanks to AI, you have better search results for products. The machine learning machines detect product pictures based on the attributes, tags, and categories you have supplied to the systems. Despite handling a massive amount of unstructured data, you can check for product availability and delivery time within minutes.

Songs and Voices

Shazam can tell you the name of the song, its lyrics, the singer’s name, and the platforms on which the music is available. The app uses AI like many other apps that can even detect the speaker or animal noise. The police department can use voice recognition systems to identify criminals in the future.

Text Recognition

Gone are the days when you do not realize who the writer is. With optical character recognition (OCR), you can detect printed types, handwriting, and texts. Someday, your ATM can scrutinize your handwritten signature in the check and provide money.

Though AI can categorize data, not all information is vital for safekeeping. Instead of devoting time to arranging each dataset, the machines are now organizing only those from the unstructured data necessary for you. It is a more efficient and less time-consuming process that we will benefit from in the digital era.

To view the original article in full, visit the following link: https://www.analyticsinsight.net/understanding-unstructured-data-using-recognition-pattern-technology/

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