What is automatic information extraction? - Advantages and techniques

Information extraction is a versatile tool that is used in many areas. It enables the collection of data from various media sources such as images, emails, PDFs and web pages. From extracting key data points from research articles to identifying trends in customer feedback, information extraction helps to process large amounts of text efficiently. 

In industries such as healthcare, finance, customer service and many others, automated information extraction is increasingly recognized as a key technology. It plays an essential role in business intelligence by enabling analysts to collect and analyze structured information from various sources. Information extraction is the crucial intermediate step where the collected information is structured before an analyst can analyze it.  Similarly, information extraction solutions identify references in scientific research. For example, in the healthcare sector, it helps to structure and summarize patient records, thereby improving the efficiency of healthcare provision.

The key benefits of information extraction include: 

-Lower operating costs: Information extraction automates processes, resulting in shorter working times and lower costs. This increase in efficiency enables companies to use resources more effectively and remain competitive. 

-Increased employee productivity: Automation enables employees to save time that they would otherwise have spent on manual data extraction. This allows them to focus on strategic and value-adding tasks. 

-Shorter turnaround times: Utilizing information extraction software can significantly speed up workflows. Instead of taking days or weeks to extract relevant data, this can be done in a matter of seconds. 

1.Manual information extraction:

Manual information extraction involves the process of collecting data from various sources by hand, without the use of automated tools. It can be very time-consuming and labor-intensive and requires careful human work and attention. This method can lead to inaccuracies and discrepancies due to the subjective aspect of manual data collection.

2. Automatic information extraction with OCR:

Optical character recognition (OCR) is the fundamental step in digital information extraction. It enables the automatic identification and extraction of text from scanned documents and images. OCR enables printed text to be efficiently recognized and converted into machine-readable data. This technology therefore represents an important step towards digitizing information from physical sources and making it accessible for further processing.

However, OCR reaches its limits when it comes to interpreting and meaningfully processing the extracted data. Human intervention is essential for the precise capture and processing of information in order to identify and correct possible errors. A purely automated approach using OCR alone is therefore not enough to fully automate the entire information extraction process chain. Humans play a crucial role in quality assurance and the correct allocation of extracted data, which significantly improves the efficiency and accuracy of the overall process.

3 AI-supported automated information extraction

AI-supported information extraction allows data to be interpreted in a way that is similar to human capabilities. Using artificial intelligence (AI), documents can be processed with high speed and precision. Intelligent Document Processing (IDP) uses advanced algorithms and machine learning to recognize, analyze and understand various documents. This technology enables flexible processing of documents with different layouts and formats.

Through continuous training with data, the AI becomes increasingly reliable and is able to recognize complex patterns and correlations. This leads to a continuous improvement in the accuracy and efficiency of data extraction, allowing companies to better optimize their processes. In contrast to pure OCR-based extraction, which only reads textual data, AI-supported information extraction enables deeper processing and interpretation of the extracted information, resulting in higher quality and decision-making capability in business processes.

Our expertise extends beyond research and consulting to include the provision of machine learning in various subject areas. With an experienced team specializing in NLP (Natural Language Processing) and ML, we develop tailor-made solutions to meet our clients' needs. 

Find out more about our information extraction projects, including automated fee billing verification and extracting information from customer queries. For more information on our previous projects, please refer to the detailed information available on our website.

dida's product for information extraction: SmartExtract

Although dida is an AI service provider, it developed its first AI product in 2024. This allows information to be extracted and structured from emails, PDFs or other file types using AI. Take a look at it if you are interested in a customized information extraction solution: https://smartextract.ai/