What is NLP?
Overview of some of the techniques used in NLP…..
What is NLP?
Natural Language Processing is the ability of the computer to understand human language as it is spoken and written. It is a part of Artificial Intelligence.
NLP is extremely popular and it is being adopted and developed constantly.
Why is NLP popular?
Most businesses generate huge amounts of unstructured, text-heavy data and there arises a need to efficiently process it.
All of the social medial platforms such as WhatsApp, Messenger, Telegram, etc constantly generate large amounts of text data every second.
Understanding and generating insights from these texts is of utmost importance to the companies and the common approach can no longer be used to understand the text. This is where NLP comes into the picture.
NLP Techniques:
Two main techniques used in NLP are syntax and semantic analysis:
Syntax Analysis:
The arrangement of words in a sentence to make grammatical sense is known as syntax. Various Syntax techniques are:
- Parsing:
Parsing is used to determine the structure of the text by analyzing the words based on their grammar. Here the sentence is broken down into the parts of speech.
2. Word Segmentation:
Here a string of text is taken and is split up into words. In other words, a sentence is split into words by recognizing the white spaces.
3. Sentence Segmentation:
Here a group of sentences is split into individual sentences based on the position of the period.
4. Morphological Segmentation:
Here the words are split into smaller parts so that algorithm can easily recognize them. Ex unavoidable is split as “un”, “avoid”, “able”.
5. Stemming:
Stemming is used to reduce a word to its root form. Ex “Jogging” is reduced to “jog”. The algorithm sees that both the above words are the same.
Semantic Analysis:
NLP uses semantic in order to understand the meaning and the structure of the sentences. Some Semantic techniques are:
- Named entity recognition:
Named entity recognition is used to locate and classify named entities in text into already defined categories such as locations, person names, quantities, etc. Ex It can be used to identify various person names from a text.
2. Word Sense Disambiguation:
Word sense disambiguation is used to find the meanings of the words based on the context in which it is used. Ex “Bark of the tree”. Here the algorithm can understand that “Bark” refers to the outermost layer of the tree and not the “barking of a dog”.
Some Applications of NLP:
- Sentiment Analysis:
Sentiment Analysis is a sub-field of NLP that tries to identify and extract opinions within a given text. Ex: a Twitter data set is used to extract the feeling or the opinion of the users on a particular event.
2. Chatbot and Assistants:
Chatbots and AI assistants are used for question answering. The chatbot needs to be able to understand what the user is messaging and reply accordingly. Therefore NLP is used here so that the text can be understood.
3. Text Summarization:
In-text summarization a bf summary of the text is extracted by maintaining the context of the original article. NLP is used to achieve this.
4. Speech Recognition:
NLP is also used in Speech Recognition in order to transform spoken language into a machine-readable format.
Hope you have understood about NLP and got an overview of some of the techniques used.
Happy Learning!!! Stay Safe!!!
