Tag Archives: Natural language processing

16Jun/23

How do you start a sentiment analysis project?

June 16, 2023 /Developers/ — Sentiment analysis is the process of determining the emotional tone of a piece of text. It is a subfield of natural language processing (NLP) that deals with identifying and extracting subjective information from text. Sentiment analysis is often used to understand customer sentiment, brand reputation, and social media trends.

There are two main types of sentiment analysis: Continue reading

20Apr/23

What Large Language Models (or LLMs) are, how they are developed, and how they work.

April 19, 2023 /Technology/ — A large language model (LLM) is a type of artificial intelligence (AI) that is trained on a massive amount of text data. This data can be anything from books and articles to social media posts and code. LLMs are able to learn the statistical relationships between words and phrases, which allows them to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. LLMs can be used for a variety of tasks, including: Continue reading

16Apr/23

Practical examples of combining Search Results with the Power of NLP (Natural Language Processing) and Semantic Knowledge

April 16, 2023 /Technology/ — We’ve all had that frustrating experience of trying to search for something and not finding the results we are after. By building systems that leverage NLP, we can infuse our systems with semantic knowledge and minimize this frustration for end users of our systems.
Free-text search can be limiting, requiring us to search using the exact set of keywords that have been indexed. To go beyond simple text matching requires an understanding of both the search intent and the semantic meaning of the words being searched.

Here are a few practical examples of combining search results with the power of NLP and semantic knowledge: Continue reading

15Aug/22

OPINION: Besides AI, regulation key to fight mis/disinformation

By Anya Schiffrin, director of the Technology, Media and Communications specialization at Columbia University’s School of International and Public Affairs.

When worries about online mis/disinformation became widespread after the 2016 U.S. election, there was hope that the tech giants would use artificial intelligence (AI) to fix the mess they created. The hope was that platforms could use AI and Natural Language Processing (NLP) to automatically block or downrank false. illegal or inflammatory content online without governments having to regulate.
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