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Applications of NLP
Table of Contents
1. MACHINE TRANSLATION
With Every growing availability of information online, the necessity to access it becomes more and more important and the value of natural language processing applications becomes evident. machine transition helps in overcoming language hurdles that we usually experience by translating technical manuals, support contents, or catalogs at a considerably smaller cost.
The challenge with machine translation technologies is not about translating words, but about comprehending the meaning of sentences to offer an exact translation.
2. AUTOMATIC SUMMARISATION
An overload of information is a big problem when we need to access a particular, essential piece of information from a huge knowledge base. Automatic summarisation is useful, not only for summarising contextual documents and information, and also for understanding the emotional meaning hidden inside the information.
Automatic summarisation is particularly useful when we wish to get an overview of the News items while avoiding redundancy from multiple sources and maximizing the diversity of the available content.
3. SENTIMENT ANALYSIS
The objective of sentiment analysis is to find sentiment among the numerous posts or even in the same post where emotion is not always clearly expressed. Companies make use of NLP applications, like sentiment analysis, to identify opinions and sentiments online in order to understand what users feel about their products and services.
Apart from determining simple polarity, sentiment analysis identifies sentiment in context to help better understand what is behind an opinion. It can be relevant in understanding the purchasing decision.
4. TEXT CLASSIFICATION
Text classification enables us to assign predefined categories to documents. It also organizes them to help us find the information we need. For example, an application of text categorization is spam filtering in email.
5. VIRTUAL ASSISTANTS
With the improvement of speech-understanding technology and voice-input applications, the importance of NLP will also increase. Virtual assistants are widely used thanks to applications, such as OK Google, chat boxes, etc.
We can use them as text-only interfaces or as spoken dialogue systems. Though they show great promise they still have a long way to go. This remains a challenge, particularly for search engines, and is one of the important applications of NLP research.
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