Clustering And Topic Modeling In NLP: What Happens If K-means And LDA Have A Competition?

One day, K-means and LDA, two popular algorithms in natural language processing (NLP), decided to have a friendly competition to see which one was better at clustering and topic modeling. K-means, known for its simplicity and speed, boasted that it could group any collection of documents in a flash. LDA, on the other hand, was confident in its ability to uncover the latent topics hidden within the data using probabilistic generative modeling.



How Do Natural Language Processing Systems Work?

Probably you are already aware of the fact that artificial intelligence and machine learning are all around us, from phones to devices and a huge number of things in between. But do you know what is the core technology that enables these devices to perform effectively? It’s natural language processing or NLP. Have you ever come across situations like you’re typing something on your smartphone and it is coming up with word suggestions based on what you’re currently typing and what you usually type? Surely you did and that’s a natural language processing system in action. We surely overlook the technology and take it for granted but in the business domain, it is one of the biggest innovations that have transformed the entire domain.



What Programming Languages Are Suitable For Natural Language Processing?

Probably you already know that natural languages, which are used by humans for communications, are difficult to define with a specific set of rules. By using the combined power of computer science, computational linguistics, and artificial intelligence, NLP or natural language processing helps machines to understand that natural language. The technique uses machine-based algorithms that have the ability to obtain meaning from communication both verbal and written. Natural language processing is widely used in language translation, recognizing human speech, information retrieval etc.

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