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Topic Modelling (NLP)

Natural Language Processing enabled Businesses to understand their documents better and empowered AI capabilities for auto-generated texts, bespoke chatbots, custom search engines, and tailored document generation. 

Language Models can be built from scratch to ensure ethical and responsible content in the model output. Still, they can also be trained on a corpus of data or fine-tuned based on language models already trained by third parties.

Fine-tuning a Language Model to reduce perplexity on niche domains, thus improving the understanding of the words in that context. As a consequence, it increases accuracy in topic modelling.

Topic modelling describes keywords frequently occurring in a corpus that indicates a category or a genre. This taxonomy is usually used to identify aspects of the business that either require attention or highlight successes, amongst other use cases. Having text transformed into categories helps link costs of operations and revenue with these topics.

NLP is also used to develop tailored search engines with bespoke and proprietary content without risking data leakage.

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