How would you design an algorithm for summarizing text?
One way of designing an algorithm for summarizing text is to first identify the important concepts in the text using a part-of-speech tagger and a lexicon. Then, use a statistical technique such as Latent Dirichlet Allocation (LDA) to group the words in the text into a few major topics. Next, take those key words and combine them into a shorter, more coherent summary of the text. Finally, use a technique such as sentence compression to remove redundant information and further shorten the summary.
My approach would be to break the text into sentences and use sentiment analysis to determine the key points. Then I would search for the most relevant sentences and use statistical natural language processing techniques to summarize the text in a concise and meaningful way.