{"id":48959,"date":"2024-04-15T22:48:53","date_gmt":"2024-04-15T22:48:53","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=48959"},"modified":"2024-04-15T22:48:53","modified_gmt":"2024-04-15T22:48:53","slug":"in-data-science-what-is-the-term-for-the-process-of-converting-text-data-into-numerical-form-while-preserving-semantic-meaning","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/in-data-science-what-is-the-term-for-the-process-of-converting-text-data-into-numerical-form-while-preserving-semantic-meaning\/","title":{"rendered":"In data science, what is the term for the process of converting text data into numerical form while preserving semantic meaning?"},"content":{"rendered":"

[amp_mcq option1=”Data aggregation” option2=”Data normalization” option3=”Word embedding” option4=”Data imputation” correct=”option3″]<\/p>\n

The correct answer is C. Word embedding.<\/p>\n

Word embedding is a technique in natural language processing (NLP) that maps words or phrases to vectors of real numbers. This allows computers to represent the meaning of words in a way that can be used for tasks such as text classification, sentiment analysis, and machine translation.<\/p>\n

Word embedding is a powerful technique that has been shown to be effective for a variety of NLP tasks. However, it is important to note that word embedding is not a perfect solution. For example, word embedding can be sensitive to the order of words in a sentence, and it can be difficult to interpret the meaning of the vectors that are produced.<\/p>\n

Despite these limitations, word embedding is a valuable tool for NLP. It can be used to represent the meaning of words in a way that can be used for a variety of tasks.<\/p>\n

Here are brief explanations of the other options:<\/p>\n