Consider the following document collection D={D1,D2, D3 } (given as one document per line): new york times new new york post the times Assume that the stopword list contains the word the, and words are not stemmed. For the given example, show the dictionary and the postings list including all the relevant statistics computed (such as tf-idf values shown explcitly as '(tf,idf)' with each document in the postings list) for implementing (uncompressed) inverted index structure for Vector Space Ranked Retrieval in an easy-to-read format. Assume that term frequency factor is the count of the number of term occurrences in a document (rather than the normalized value) and the inverse document frequency factor is the reciprocal of the fraction of documents that contain the term (rather than its logarithm). What are the relevance scores and the "relative" ranking of the documents for the query new