please I need answer this question java programming DAT/305

import java.util.ArrayList; import java.util.Iterator;

public class SuggestionFrames { /** * This method gets the visiting customer index and the product index of requested page * and using previous data collected it produces product suggestions from the same seller * or brand * * @param currentProductIndex the product index of requested web page (at least 11) * @param currentCustomerIndex the visiting customer * @param customerBehaviorMatrix the previous data collected * @param orderedProductList list of all products ordered wrt dataMatrixIndex of product * * @return list of 5 product to be suggested from same brand/seller/manufacturer; * not containing the product of requested page, and if suggestions are less than 5 * products from same brand/seller/manufacturer are added to the list until list size is five. */ public ArrayList otherProductsOfTheSellerList(int currentProductIndex, int currentCustomerIndex, double[][] customerBehaviorMatrix, ArrayList orderedProductList) { //define return index; 5 products /* * find product from index; product list is ordered wrt column index * so list index will be 11 smaller */

//find the most similar other customer //get current customer vector

//get similar customer vector

//find suggestions //start from 10 since the first 10 columns are not products

//product list is ordered wrt column index so list index will be 10 smaller

//remove excess if list is larger than 5

// and add if list is smaller than 5

return null; } /** * This method gets the visiting customer index and the product index of requested page * and using previous data collected it produces product suggestions based on previous * sales of similar customer * * @param currentProductIndex the product index of requested web page (at least 11) * @param currentCustomerIndex the visiting customer * @param customerBehaviorMatrix the previous data collected * @param orderedProductList list of all products ordered wrt dataMatrixIndex of product * * @return list of 5 product to be suggested based on previous sales of similar customer; * not containing the product of requested page, and if suggestions are less than 5, * more products are added to the list until list size is five. */ public ArrayList interestedProductsSuggestionList(int currentProductIndex, int currentCustomerIndex, double[][] customerBehaviorMatrix, ArrayList orderedProductList) { //define return index; 5 products

/* * find product from index; product list is ordered wrt column index * so list index will be 11 smaller */

//find the most similar other customer

//get current customer vector

//get similar customer vector

//find suggestions //start from 10 since the first 10 columns are not products

//product list is ordered wrt column index so list index will be 10 smaller

//remove excess if list is larger than 5 // and add if list is smaller than 5

return null; } }