Text Annotation2019-09-06T11:41:31+02:00
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Text Annotation

It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout.

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We are currently living in an age where computers are learning and exploring the physical world in order to properly identify and classify all of the objects they detect. In this regard, they are similar to human beings because we also relied on the help of others to teach us about all of the things that exist in the world when we were children. Therefore, properly labelling all of the data that you use for machine learning is critical for the successful outcome of your project. You need to make it easier for computers to learn and understand the data so the computer can find patterns and inferences. This is usually done by adding metadata to the dataset.

Label Tag

Optical Character Recognition (OCR) is taking all of the images of texts, regardless of whether they were printed, handwritten or typed into editable text formats. Such text recognition software is already being used across industries such as banking, legal, healthcare and many others. This technology eliminates the need to retype documents, waste money space on storing them and makes the data contained in the documents widely accessible. We can provide you with a database which can be used to train your machine learning algorithms to recognize all kinds of characters.

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In order for your documentation to be usable, you will need accurate and timely transcriptions. We are committed to providing you with expedient transcription services at the highest possible quality. We can provide you with the full scope of OCR Transcription services handled by skilled professionals thus reducing the total cost of data entry. By allowing us to shoulder the load of data entry, you can focus more attention on developing your product.

and categorization

Text classification is assigning certain tags or categories depending on the content. There are wide uses of this technology for labelling topics, detecting spam and the intent. It could provide your business with valuable insights by extracting information from social media accounts, customer service, customer feedback and many other sources. Making sense of such a deluge of data can be extremely time-consuming. With text categorization it can be done in a matter of minutes.

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Label Tag
Named-entity recognition (tagging)

Have you ever wondered which websites mention your company? In fact, it does not even have to be your company but rather a product, employee name or any other entity. If you manage a large company, people on the other side of the world could be discussing your brand on forums, social media and other platforms which will open up new markets and business opportunities.

Sentiment analysis

Imagine a computer understanding the opinion of a given text on any subject. This is possible with text sentiment analysis. Recent advancements in machine learning have turned what was once a sci-fi fantasy into reality. In addition to identifying the opinion, sentiment analysis is capable of identifying:

  • Polarity – Determine whether the opinion is positive or negative in nature
  • Subject – Exactly what is being discussed in the text
  • Speaker – Who is the person that expresses their opinion

Since sentiment analysis has many practical applications, it has attracted the attention of businesses and developers alike. For example, it can scan all of the reviews left on a restaurant’s website, identify the polarity of the review as well as other factors, categorize the reviews and report all of the findings back to you.

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