Natural Language Processing Flashcards
What was one of the first notable contributions to NLP?
The Turing Test developed by Alan Touring. This test measures a machine’s ability to answer any question in a way that’s indistinguishable from a human.
List common analysis techniques used in NLP. (3)
- Sentiment analysis
- Intent analysis
- Context analysis
Sentiment analysis: Involves determining whether a piece of text (such as a sentence, a social media post, a review, or a tweet) expresses a positive, negative, or neutral sentiment. A sentiment is a feeling or an attitude toward something. For example, sentiment analysis can determine if this customer review of a service is positive or negative: “I had to wait a very long time for my haircut.” Sentiment helps identify and classify emotions or opinions in text to help businesses understand how people feel about their products, services, or experiences.
Intent analysis: Intent helps us understand what someone wants or means based on what they say or write. It’s like deciphering the purpose or intention behind their words. For example, if someone types, “I can’t log in to my account,” into a customer support agent, intent analysis would recognize that the person’s intent is to get help to access their account. The agent might reply with details about resetting a password or other means the user can try to access their account. AI assistants often use intent analysis to understand user requests and provide appropriate responses or actions.
Context (discourse) analysis: Natural language relies heavily on context. The interpretation of a statement might change based on the situation, the details provided, and any shared understanding that exists between the people communicating. Context analysis involves understanding this surrounding information to make sense of a piece of text. For example, if someone says, “They had a ball,” context analysis can determine if they are talking about a fancy dance party, a piece of sports equipment, or a whole lot of fun. It does this by considering the previous conversation or the topic being discussed. Context analysis helps NLP systems interpret words more accurately by taking into account the broader context, the relationships between words, and other relevant information.
These three analysis techniques–sentiment analysis, intent analysis, and context analysis–play important roles in extracting valuable insights from text and speech data. They create a more sophisticated and accurate understanding and engagement with textual content in various applications of NLP.
How does NLG and NLU process information?
NLG: Structured to Unstructured
NLU: Unstructured to Structured
