id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_uwalrhrrubc2nc6hsopdwz6rte	Punam Bedi	Trust based recommender system using ant colony for trust computation	2012	3	.pdf	application/pdf	2008	152	55	Collaborative Filtering (CF) technique has proven to be promising for implementing large scale recommender systems but its success depends mainly on locating similar neighbors. our proposed Trust based Ant Recommender System (TARS) produces valuable recommendations by trust graph from where recommendations are generated, items and number of neighbors involved in predicting ratings can help active user make better decisions. Also, new users can highly benefit from pheromone updating strategy known from ant algorithms as positive feedback in the form of aggregated dynamic trust pheromone defines ''popularity'' of a user as recommender over a period of time. Filtering, Content based approach and Hybrid methods are the prevalent three approaches to developing recommender systems. There are several limitations and challenges to CF based recommender systems due to traditional emphasis on user similarity. For example, the trust intensity between recommender and active user may increase or decrease depending on TARS (Trust based Ant Recommender System), sparseness in user	./cache/work_uwalrhrrubc2nc6hsopdwz6rte.pdf	./txt/work_uwalrhrrubc2nc6hsopdwz6rte.txt