TY - JOUR ID - 91457 TI - PBloofi: An Enhanced Version of BloofI in Recommender Systems JO - International Journal of Web Research JA - IJWR LA - en SN - 2645-4335 AU - Farahi, Zahra AU - Moeini, Ali AU - Kamandi, Ali AU - Shabankhah, Mahmood AU - Hosseini, Seyed Mohsen AD - School of Engineering Science, College of Engineering, University of Tehran AD - School of Engineering Science, College of Engineering, University of Tehran Tehran, Iran Y1 - 2018 PY - 2018 VL - 1 IS - 2 SP - 17 EP - 26 KW - Recommender systems KW - Bloom Filter KW - Hierarchical Bloom filter DO - 10.22133/ijwr.2018.91457 N2 - In this paper, we focus on improving the performance of recommender systems. To do this, we propose a new algorithm named PBloofI which is a kind of hierarchical bloom filter. Actually, the Bloom filter is an array-based technique for showing the items’ features. Since the feature vectors of items are sparse, the Bloom filter reduces the space usage by using the hashing technique. And also, to reduce the time complexity we used the hierarchical version of bloom filter which is based on B+ tree of order d. Since Bloom filters can make a tradeoff between space and time, proposing a new hierarchical Bloom filter causes a remarkable reduction in space and time complexity of recommender systems. To increase the accuracy of the recommender systems we use Probabilistic version of hierarchical Bloom filter. By measuring the accuracy of the algorithm we show that the proposed algorithms not only decrease the time complexity but also have no significant effect on accuracy. UR - https://ijwr.usc.ac.ir/article_91457.html L1 - https://ijwr.usc.ac.ir/article_91457_2859c8be740ec256d977c4c0f28c66f9.pdf ER -