Abstract
paper, real estate problem, n-most demanding products (n-MDP) discovering, is formulated. A set of customers demanding a real estate product with multiple features, there are existing products in market, preferred products set which is offered by the company, and a positive integer n, which will be found to help the company to select n products from preferred products such that expected number of the total customers for the n products is maximized. Here it is shown the problem is NP-hard when the number of features for a product is 3 or more. Bit Map Index (BMI) is developed on the customer requirements and products of real estates. The Output of the BMI is given as an input to the algorithm like Apriori. An Apriori algorithm proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. An Apriori Algorithm is provided to find the optimal solution of the problem by using the pruning strategy. The n value is determined by the algorithm which will help the company to maximize the product.
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