Deep Learning for NLP: Text Summarization Quiz

What is the process of creating shorter and concise versions of texts from large texts for quicker consumption?

• Text Generation

• Text Analysis

• Text Extraction

• Text Summarization

What is the main goal of text summarization?

• To create longer texts from shorter texts

• To extract irrelevant information from the original text

• To create shorter and concise versions of texts

• To translate texts into different languages

Which type of summarization generates summaries by rearranging important sentences from the original text?

• Abstractive Summarization

• LSA Summarization

• Extractive Summarization

• TextRank Summarization

What is the main approach of the Luhn method for text summarization?

• Vector-based Algorithm

• Frequency Method

• TF-IDF

• Cosine Similarity

Which library can be used to implement various summarization algorithms such as TextRank, Luhn, and LSA?

• Sumy

• NLTK

• TensorFlow

• PyTorch

What is the main goal of abstractive summarization?

• To generate summaries from scratch without reusing phrases from the original text

• To extract important sentences from the original text

• To rearrange sentences from the original text

• To summarize the text based on frequency of words

What are the three main aspects of the seq2seq model for text summarization?

• LSTM, Bi-directional LSTM, Uni-directional LSTM

• TF-IDF, POS tags, Word Embeddings

• Sumy, Luhn, TextRank

• Encoder, Decoder, Attention Mechanism

What is the purpose of the attention mechanism in text summarization?

• To reduce the complexity of the model

• To limit the information available to the decoder

• To access intermediate hidden states in the encoder

• To create a bottleneck for information

What is the main goal of the attention mechanism in text summarization?

• To focus on the entire input sequence

• To predict a word based on the entire input sequence

• To focus on specific sequences from the input

• To ignore the input sequence completely

What is the main approach of the LSA method for text summarization?

• Cosine Similarity

• Frequency Method

• Vector-based Algorithm

• Latent Semantic Analysis