How Can We Use NLP to Understand the Emergence of Network Ties?
Session Number
Project ID: CMPS 24
Advisor(s)
Dr. Noshir Contractor, Jane S. & William J. White, Northwestern University, McCormick School of Engineering
Discipline
Computer Science
Start Date
17-4-2024 10:00 AM
End Date
17-4-2024 10:15 AM
Abstract
The study of computer-human natural language interaction is the focus of the artificial intelligence field known as natural language processing (NLP). It entails creating models and algorithms that let computers comprehend, interpret, and produce human language. Language translation, emotion analysis, chatbots, speech recognition, and text summarization are just a few of the many uses for NLP. Natural language processing was founded in the 1940s to find a way to translate text between languages automatically. Since then, NLP has been a fundamental tool for the success of many different kinds of AI. The capacity of Natural Language Processing (NLP) to comprehend, interpret, and produce human language makes it applicable to a wide number of contexts. In machine translation programs like Google Translate, NLP is used to translate text between languages. It provides information, answers queries, and helps consumers through chatbots and virtual assistants like Siri, Alexa, and website chat interfaces. With natural language processing (NLP), organizations may better comprehend social media conversations, reviews, and consumer feedback by analyzing text's sentiment or emotional tone. In this paper, we will summarize research and its impact on the innovation of NLP, as well as identify possible areas of study for the future.
How Can We Use NLP to Understand the Emergence of Network Ties?
The study of computer-human natural language interaction is the focus of the artificial intelligence field known as natural language processing (NLP). It entails creating models and algorithms that let computers comprehend, interpret, and produce human language. Language translation, emotion analysis, chatbots, speech recognition, and text summarization are just a few of the many uses for NLP. Natural language processing was founded in the 1940s to find a way to translate text between languages automatically. Since then, NLP has been a fundamental tool for the success of many different kinds of AI. The capacity of Natural Language Processing (NLP) to comprehend, interpret, and produce human language makes it applicable to a wide number of contexts. In machine translation programs like Google Translate, NLP is used to translate text between languages. It provides information, answers queries, and helps consumers through chatbots and virtual assistants like Siri, Alexa, and website chat interfaces. With natural language processing (NLP), organizations may better comprehend social media conversations, reviews, and consumer feedback by analyzing text's sentiment or emotional tone. In this paper, we will summarize research and its impact on the innovation of NLP, as well as identify possible areas of study for the future.