


What is an Evoked Set in NLP and IR?
In the context of computer science and artificial intelligence, "evoked set" refers to a specific technique used in natural language processing (NLP) and information retrieval.
The evoked set is a set of words or phrases that are associated with a particular concept or idea, and are likely to be used by people when discussing that concept. For example, if we were talking about the concept of "car," the evoked set might include words like "vehicle," "automobile," "motor vehicle," etc.
The evoked set is typically derived from a large corpus of text data, such as a collection of books or articles, and is used to help train machine learning models for tasks such as text classification, sentiment analysis, and information retrieval. By analyzing the patterns of language use in the evoked set, these models can learn to recognize and understand the concepts and ideas that are being discussed in text data.
In summary, the evoked set is a set of words and phrases that are associated with a particular concept or idea, and are likely to be used by people when discussing that concept. It is a useful tool for natural language processing and information retrieval tasks, and can help machine learning models better understand the meaning and context of text data.



