Course Content
Extracting Text Meaning using TF-IDF
Score Sentences
Having established the TF-ISF scores for individual words within sentences, our next step transitions from a word-centric analysis to evaluating entire sentences.
Summarizing Sentence Significance
The essence of calculating sentence scores lies in aggregating the TF-ISF scores of all words within a sentence. This cumulative approach allows us to assess the sentence's overall informational value to the text.
For each sentence, we calculate its total TF-ISF score by summing up the TF-ISF scores of all the words it contains.
This is achieved by iterating through the list of dictionaries (tf_isf_scores), each representing a sentence's word scores, and summing these scores. The result is a list (sentence_scores) where each element corresponds to the total TF-ISF score of a sentence.
Task
Calculate the total score for each sentence using the TF-ISF scores.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
Having established the TF-ISF scores for individual words within sentences, our next step transitions from a word-centric analysis to evaluating entire sentences.
Summarizing Sentence Significance
The essence of calculating sentence scores lies in aggregating the TF-ISF scores of all words within a sentence. This cumulative approach allows us to assess the sentence's overall informational value to the text.
For each sentence, we calculate its total TF-ISF score by summing up the TF-ISF scores of all the words it contains.
This is achieved by iterating through the list of dictionaries (tf_isf_scores), each representing a sentence's word scores, and summing these scores. The result is a list (sentence_scores) where each element corresponds to the total TF-ISF score of a sentence.
Task
Calculate the total score for each sentence using the TF-ISF scores.
Switch to desktop for real-world practiceContinue from where you are using one of the options below