id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_gxb3jgybnreolk7frlfntepowa	T Roh	The collaborative filtering recommendation based on SOM cluster-indexing CBR	2003	11	.pdf	application/pdf	7726	692	61	processes, Self-Organizing Map (SOM) and Case Based Reasoning (CBR) by changing an unsupervized clustering problem into a supervized recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference. Keywords: Collaborative filtering; Recommendation system; Self-organizing map; Case-based reasoning based on preference ratings information to match users with recommend items that those similar users like (Breese, item or page, the ratings of users, content-based filtering, information about each item in predicting user preferences. most similar cluster is inferred from reference users indexed The process of the cluster-indexing method is exemplified in Fig. 4 If an active user's preference rating {5, _, 2, Computation example of SOM cluster-indexing CBR CF model. SOM cluster-indexing CBR CF model Proposed model SCP SOM cluster-indexing CBR CF predictor The collaborative filtering recommendation based on SOM cluster-indexing CBR SOM cluster-indexing CBR CF recommendation SOM cluster-indexing CBR CF recommendation	./cache/work_gxb3jgybnreolk7frlfntepowa.pdf	./txt/work_gxb3jgybnreolk7frlfntepowa.txt