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Authors: David Ben Shimon ; Lior Rokach ; Bracha Shapira and Guy Shani

Affiliation: Ben Gurion University of the Negev, Israel

Keyword(s): Item-Based, Locality Sensitive Hashing, Collaborative-Filtering, top-N recommendations

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Industrial Applications of AI ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: Item-based Collaborative Filtering (CF) models offer good recommendations with low latency. Still, constructing such models is often slow, requiring the comparison of all item pairs, and then caching for each item the list of most similar items. In this paper we suggest methods for reducing the number of item pairs comparisons, through simple clustering, where similar items tend to be in the same cluster. We propose two methods, one that uses Locality Sensitive Hashing (LSH), and another that uses the item consumption cardinality. We evaluate the two methods demonstrating the cardinality based method reduce the computation time dramatically without damage the accuracy.

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Paper citation in several formats:
Ben Shimon, D.; Rokach, L.; Shapira, B. and Shani, G. (2015). Fast Item-Based Collaborative Filtering. In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-074-1; ISSN 2184-433X, SciTePress, pages 457-463. DOI: 10.5220/0005227104570463

@conference{icaart15,
author={David {Ben Shimon}. and Lior Rokach. and Bracha Shapira. and Guy Shani.},
title={Fast Item-Based Collaborative Filtering},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2015},
pages={457-463},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005227104570463},
isbn={978-989-758-074-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Fast Item-Based Collaborative Filtering
SN - 978-989-758-074-1
IS - 2184-433X
AU - Ben Shimon, D.
AU - Rokach, L.
AU - Shapira, B.
AU - Shani, G.
PY - 2015
SP - 457
EP - 463
DO - 10.5220/0005227104570463
PB - SciTePress