Which of the following statement about text analysis is incorrect? O We can use supervised learning, semi-supervised learning, or unsupervised learning for text analysis When we have enough training data, supervised

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Question 8
Which of the following statement about text
analysis is incorrect?
We can use supervised learning, semi-supervised
learning, or unsupervised learning for text analysis
When we have enough training data, supervised
learning method is the best choice
When we don't have any labeled data, we can
either choose semi-supervised learning or
unsupervised learning methods
Bootstrapping is frequently used for semi-
supervised learning
Transcribed Image Text:Question 8 Which of the following statement about text analysis is incorrect? We can use supervised learning, semi-supervised learning, or unsupervised learning for text analysis When we have enough training data, supervised learning method is the best choice When we don't have any labeled data, we can either choose semi-supervised learning or unsupervised learning methods Bootstrapping is frequently used for semi- supervised learning
Question 9
Which of the following models can be used for
calculating document similarity?
Training a word2vec model on the corpus that
learns context present in the document
Training a bag of words model that learns
occurrence of words in the document
Creating a document-term matrix and using
cosine similarity for each document
All of the above
Transcribed Image Text:Question 9 Which of the following models can be used for calculating document similarity? Training a word2vec model on the corpus that learns context present in the document Training a bag of words model that learns occurrence of words in the document Creating a document-term matrix and using cosine similarity for each document All of the above
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