@inproceedings{4e9aa40d7fd54a74b0b90cb13f5c24b2,
title = "Recommendations meet web browsing: Enhancing collaborative filtering using internet browsing logs",
abstract = "Collaborative filtering (CF) recommendation systems are one of the most popular and successful methods for recommending products to people. CF systems work by finding similarities between different people according to their past purchases, and using these similarities to suggest possible items of interest. In this work we show that CF systems can be enhanced using Internet browsing data and search engine query logs, both of which represent a rich profile of individuals' interests.",
author = "Royi Ronen and Elad Yom-Tov and Gal Lavee",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 32nd IEEE International Conference on Data Engineering, ICDE 2016 ; Conference date: 16-05-2016 Through 20-05-2016",
year = "2016",
month = jun,
day = "22",
doi = "10.1109/ICDE.2016.7498327",
language = "الإنجليزيّة",
series = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",
pages = "1230--1238",
booktitle = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",
}