The Construction of a Cost-Efficient Optical Character Recognition Active Learning Pipeline by United Airlines Using Amazon Web Services
In today’s digital age, businesses are constantly seeking ways to streamline their operations and improve efficiency. One area where this is particularly important is in data processing and analysis. United Airlines, one of the world’s largest airlines, has recently implemented a cost-efficient optical character recognition (OCR) active learning pipeline using Amazon Web Services (AWS) to enhance their data processing capabilities.
OCR technology is used to convert different types of documents, such as invoices, receipts, and boarding passes, into machine-readable text. This enables businesses to automate data extraction and analysis, saving time and reducing errors. However, OCR systems often require significant amounts of labeled training data to achieve high accuracy levels. This is where active learning comes into play.
Active learning is a machine learning technique that allows the system to actively select the most informative samples for labeling, reducing the amount of labeled data required. By using active learning in combination with OCR technology, United Airlines aimed to improve the accuracy of their OCR system while minimizing the cost and effort associated with manual labeling.
To construct their cost-efficient OCR active learning pipeline, United Airlines leveraged the power of AWS. AWS provides a wide range of cloud-based services that enable businesses to build scalable and cost-effective solutions. United Airlines utilized several AWS services to implement their pipeline.
Firstly, they used Amazon S3 (Simple Storage Service) to store their large dataset of unlabeled documents. Amazon S3 provides secure, durable, and highly scalable object storage, allowing United Airlines to easily manage and access their data.
Next, they employed Amazon Textract, an AWS service that uses machine learning to automatically extract text and data from documents. Amazon Textract was integrated into the pipeline to perform the initial OCR on the unlabeled documents, generating machine-readable text.
To implement the active learning component, United Airlines utilized Amazon SageMaker. Amazon SageMaker is a fully managed machine learning service that provides developers and data scientists with the tools to build, train, and deploy machine learning models. United Airlines used SageMaker to train their OCR model using the initial OCR results from Amazon Textract.
The active learning process involved iteratively selecting a subset of the unlabeled documents that were most likely to improve the OCR model’s performance. These selected documents were then manually labeled by human annotators. The labeled data was used to retrain the OCR model, improving its accuracy.
To manage the labeling process efficiently, United Airlines utilized Amazon Mechanical Turk, a crowdsourcing marketplace. Mechanical Turk allowed them to easily distribute the labeling tasks to a large pool of workers, ensuring quick turnaround times and cost-effective labeling.
Throughout the pipeline, United Airlines made use of AWS Lambda, a serverless computing service, to automate various tasks and ensure smooth integration between different components. AWS Lambda allowed them to execute code without provisioning or managing servers, reducing operational overheads.
By constructing this cost-efficient OCR active learning pipeline using AWS services, United Airlines achieved significant improvements in their data processing capabilities. The active learning approach reduced the amount of labeled data required, saving time and resources. The integration of Amazon Textract and SageMaker enabled accurate OCR results and efficient model training. Additionally, the use of Mechanical Turk and Lambda ensured seamless workflow management.
In conclusion, United Airlines’ implementation of a cost-efficient OCR active learning pipeline using Amazon Web Services showcases the power of cloud-based solutions in enhancing data processing capabilities. By leveraging AWS services, businesses can streamline their operations, improve accuracy, and reduce costs. This innovative approach by United Airlines serves as an example for other organizations seeking to optimize their data processing workflows.
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