Natural Language Processing (NLP) is a field of artificial intelligence (AI) that focuses on the interaction between computers and human language. The goal of NLP is to enable computers to understand, interpret, and generate human language in a way that is natural for humans. This article provides a detailed technical overview of NLP, including its
Large Language Models (LLMs) represent a revolutionary technology in the fields of artificial intelligence and natural language processing. These models, trained on vast amounts of textual data, have the ability to understand, generate, and process human language with a high level of accuracy and naturalness. In this article, we will explore the technical aspects of
Categorizing (or tagging) surveys is one of the fundamental tasks you’ll need to perform when working with customer (and employee) experience. It’s also an activity that takes up a significant amount of time. On the other hand, it is crucial to have feedback properly categorized to be able to work with it effectively. InsightSofa addresses
What is the Overall Experience Score (OES)? The Overall Experience Score (OES) is an innovative methodology for measuring and managing customer and employee experience, developed by InsightSofa. This methodology uses artificial intelligence to analyze the entire survey, including all questions and answers, to assign an overall survey rating on a scale from 0 to 10.
The Sentiment Segment Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a crucial role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer sentiment
The AI Sentiment Evolution Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a key role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer
