Data Capture Extraction: Data capture projects can involve all types of data, presented in different forms and formats. No matter the scope of your data capture project. We can handle all types of tasks from manual data entry to data capture from documents or scans using optical character recognition (OCR). The world around us is fill with information. Valuable data is lock in silos such as emails, screenshots and the web. Capturing and extracting that information in order to process it, make sense of it. And use it to help us make better and inform decisions should be fun and stimulating. Email has become a pillar of our modern and connect society. And it now serves as a primary means of communication.
An email can be divide into several parts: subject, body, attachments, sender and receiver(s). We should also note that the headers section reveals important information. About the mail servers involve in the process of sending and receiving an email. Before addressing how we can extract information from each part of an email. We should understand that a mailbox can be view as a semi structure database. That does not use a native querying language (e.g., SQL) to extract information. Using our knowledge of the data types for email elements, we can determine how to treat each element. And predict the type of data we can expect to extract.
In order to connect to a mail server and extract data, we will be using a cross-platform C# library call MailKit. Extracting meaning from text is a fascinating topic, whether we are examining how to extract specific data types, recognize entities, or classify words within text. When you are able to make sense of extract data, you have access to a powerful tool that can help you improve, accelerate, and automate business processes. In fact, there is an unlimit potential of processes—from spam filters to text classification and beyond—that organizations can streamline and improve. We‟ve only scratch the surface of what is possible with powerful C# code implementations.
Table of Contents:
2:Extracting Data from Emails
3:Extracting Data from Screenshots
4:Extracting Data from the Web
5:Extracting Meaning from Text