Real Estate Loan Knowledge-Based Recommender System

Abstract

In decision making, the decision-makers frequently employ and perform routine tasks. These processes normally are time-intensive, complex, and in most cases occur regularly. To address this challenge decision makers reuse the already successful decisions. During difficult times, such actions may lead to save time, energy and man-hours, and also result in effective decision making. Memory building depends on how we successfully store earlier knowledge. We through this work introduce a recommender system which is names as BLKBRS which utilized the earlier successful models. In this work we use a case of bank loan and experimented using a semi-structured multiple attribute recommendation environment, and equate the RL-KBRS with a conventional case based reasoning system. RL-KBRS will compensate for lack of experience of young bank consultants, which permits the spread of knowledge distribution to other banks. Subject Categories and Descriptors [H.3] Information Storage and Retrieval; [I.2] Artificial Intelligence General Terms: Memory-based Approach, Information Search, and retrieval, Recommending systems, Case-Based Reasoning