Could you elaborate on the significance of tf-idf in natural language processing?
How does the tf-idf algorithm rank words based on their importance in a document and what is the range of values for tf-idf scores?
As an expert in information retrieval, could you share how tf-idf can be used to identify relevant content among the millions of data available on the internet?
What is the impact of stop-word removal on tf-idf analysis?
Why tf-idf is considered better than other techniques to determine the relevance of a document based on search queries?
How can tf-idf help increase the accuracy of text classification and clustering algorithms?
In your opinion, which applications of tf-idf are the most successful in text mining, and why?
Can you explain how tf-idf works in detail?