Understanding Word Representations

What are dense vectors in the context of teaching a computer the meaning of words?

• Unique number codes that capture meaning

• Simple lists of words

• Random numbers assigned to words

• None of the above

How does SVD help in analyzing a term-document table?

• By cleaning up and reducing the table

• By adding more data to the table

• By ignoring the relationships between words

• By creating a new table

What is the purpose of LSA in relation to SVD?

• To identify hidden meanings in text

• To create new words

• To summarize the table

• To ignore word relationships

What does the Skip-gram method do?

• Predicts context words from a target word

• Predicts a target word from context words

• Ignores word relationships

• Creates random word associations

What is the main difference between Skip-gram and CBOW?

• Skip-gram predicts context from target, CBOW does the reverse

• CBOW is slower than Skip-gram

• Both methods are identical

• Skip-gram uses more data than CBOW

What is a real-world application of Skip-gram and CBOW?

• Google's Word2Vec tool

• Creating random sentences

• Ignoring word meanings

• None of the above

What role does dimensionality reduction play in SVD?

• It increases the complexity of the data

• It simplifies the data representation

• It eliminates the need for data analysis

• It creates more dimensions in the data

How does LSA utilize SVD for text analysis?

• By clustering similar documents

• By generating random text

• By ignoring the context of words

• By creating a new language

What is the significance of word embeddings in natural language processing?

• They provide a way to represent words in a continuous vector space

• They are only used for text classification

• They replace the need for any machine learning algorithms

• They are random strings of characters

What is the primary function of word embeddings in machine learning?

• To convert words into numerical vectors

• To create visual representations of text

• To generate random text

• To ignore the context of words