TF-IDf problem help!

Write a program/class called docIndex that reads the provided input data and creates two indices, as dened below:

(a) Word / Posting Index: An inverted index (that excludes stop words from the le stoplist.txt) of terms/words and the corresponding frequency and documents in which the term is found. The index data structure should have some form such that you have random look-up of terms and allows new terms to be added without rebuilding it completely. The index should contain the document frequency of each term (i.e. the number of documents that contain the term).

(b) Document index: An inverted index that contains the number of terms in each document.

Test Program Write a program/class called test which will utilize the created indices to compute the tf-idf term weightings. Prompt the user for a term. If the term is in the word index, the program should display a list of the postings for that term. For each posting, it should generate the term weightings, tf, idf, and tf-idf in that order separated by commas. If the term is not in the inverted le, it should display a suitable message. The program should loop until the user enter QUIT.

term #docs postings apple 100 Linked list of postings 5 100 7 56 docID docFreq docID #terms in doc 106