@article {784,
	title = {	 Real Estate Loan Knowledge-Based Recommender System-},
	journal = {Journal of Digital Information Management},
	volume = {18},
	year = {2020},
	month = {04/2020},
	pages = {65-77},
	type = {Research},
	chapter = {65},
	abstract = {<p>\&nbsp;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.</p>
},
	doi = {https://doi.org/10.6025/jdim/2020/18/2/65-77},
	url = {http://dline.info/fpaper/jdim/v18i2/jdimv18i2_3.pdf},
	author = {Abdelkader Adla}
}
