How Does Data Annotation Enhance Experience for End Users

How Does Data Annotation Enhance Experience for End Users?

Artificial intelligence and machine learning have become the modern pillars of technology. They have become an integral part of every industry ranging from e-commerce services to the IT sector. Machine learning has made most of the tasks automated and easy for different industries. It has also reduced the workforce in industries as many of the tasks that the employees earlier performed are completed by various AI and ML models with greater accuracy. For example, chatbots, self-driving cars, language translators, and industrial robots. The primary requirement for training a machine learning model is the right kind of data and data management services. But sometimes, the data may not be available for the purpose you are trying to train your model. For such purposes, you have to generate the required data by yourself.

If you are working with the applications like image classification, language translators, self-driving cars, or chatbot services, then you have to deal with complex data like images, videos, or text files. You need to annotate this data using various data annotation services and then train your model using this annotated data. This data annotation is responsible for major of the present automation. Moreover, data management services have enhanced the user’s experience to a great extent. If you are confused about whether you go for the data annotation or not, you are at the right place. We will now discuss how data annotation enhances the end-user experience.

What is data annotation?

Data annotation services refer to the process of labeling various objects in images, videos, or text. The annotation is done by drawing squares around different objects in the image and labeling them with the corresponding names. The annotation can also be performed in the videos to perform classification on various frames of the video. The annotated data is used to train the ML model for image classification tasks like identifying the dogs and cats from a given image. The video annotation is useful in real-time or dynamic applications like self-driving cars. The videos provide more accuracy in the classification as compared to the images. 

Data annotation is also applied to text data for identifying the paragraph split, textual errors, and presence of particular words. It is used in data translation, checking plagiarism, vulgar content, identifying threatening dialogues, etc. The best example of text annotation is the tagging of tweets as inappropriate by Twitter based on the presence of certain words. Moreover, Google Translate is also a text annotation-based application.

How is user experience enhanced by data annotation?

Data annotation services are the pillar of every automation technology prevailing in the present world. It is the base for training the ML models for most modern technologies, including translation, automation, chatbots, text-filtering, visual-searching, etc. The data annotation services and data management services are helping the organizations of various industries to enhance their user’s experience. Let’s discuss the various fields in which data annotation is enhancing the user’s experience:

Visual search

Visual search has made searching on search engines very easy. Google lens is the best use of data annotation services for visual search. Moreover, many E-commerce platforms provide the facility of searching for a particular object by just uploading the required image. You can easily search for a particular maths problem by uploading the problem on various problem-solving sites.

Text-filtering

Social media websites keep blocking hazardous posts, threatening dialogues, vulnerable videos, pornography content, and age-restricted content. The plagiarism of content is checked by comparing the content with various websites. Spam and profanity are filtered and marked as inappropriate by various websites.

Typing suggestions

Whether the user is writing a text message or writing an e-mail, the users receive the typing suggestions corresponding to previously typed words. Moreover, when the user tries to search for something in the search engine, it automatically displays the various suggestions to complete the sentences.

Facial recognition 

The face unlocks feature in mobile and other devices have become a vital part of smartphones. It reduces the user’s tedious work of writing the whole password. The facial recognition system is also used in facebook’s person auto-tagging feature. 

Object classification

It is the main application of data annotation services. Object classification is used in traffic cameras, self-driving cars, obstacle detectors, activity detection, etc. Google photos use object classification to classify the photos according to different objects in the photo.

Chatbots

Chatbots are used by most companies to ease communication with their customers. The banks use chatbots to make the customers aware of present offers and services. The chatbots minimize human intervention and are available 24 hours to solve user queries.

Data mapping

The data annotation on text data provides the user with many data mapping services like language translation. Google translate is the best example where you can convert textual data from one language to language. Many other websites help you to convert your whole paragraph into a summary or normalize your raw data.

Conclusion

Data annotation services provide automation in various domains and industries. It can be applied to any textual, image, or video data. The data annotation is used to create translators, chatbots, automation tools, object detectors, face recognition systems, and plagiarism checkers. It is also used on social media sites to filter tweets or posts into various categories. It also helps in the classification of e-mail into various categories like spam, primary, social and promotional.

Christophe Rude
Christophe Rude
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