Results for tag: "Stemming"

Stemming is a process within Natural Language Processing (NLP) that involves reducing words to their root form. This is done by removing affixes, such as prefixes and suffixes, from words. Stemming is used to normalize words for easier comparison and analysis. It is also used to reduce the size of a corpus, or collection of documents, by removing duplicate words. Stemming is used in a variety of applications, such as search engine optimization, text classification, and sentiment analysis. It is also used in machine translation, where it helps to reduce the size of the vocabulary needed to translate a document. There are a number of companies in the stemming market, including OpenText, Lexalytics, and TextRazor. These companies provide stemming services and software to help organizations analyze and process text data. Show Less Read more