A Method for Recommending the Latest News Articles via MinHash and LSH

Title
A Method for Recommending the Latest News Articles via MinHash and LSH
Author
김상욱
Keywords
Recommendation Method; News Articles,; Latest News Articles; MinHash; LSH
Issue Date
2015-01
Publisher
ACM ICUIMC
Citation
ACM IMCOM 2015 - Proceedings 8 January 2015, Article number a60, Page. 1-6
Abstract
Since most users are more interested in the latest news articles that are recently updated, it is important to recommend those news articles to appropriate users. However, existing methods cannot recommend the latest news articles in a short time. This paper proposes a novel recommendation method focusing on the latest news articles. It spends much shorter execution time than the existing methods thanks to employing two approximation methods, MinHash and locality sensitive hashing. For evaluation, we conducted extensive experiments using a real-world dataset. The experimental results show that our method provides better accuracy and performs much faster than the existing methods.
URI
http://hdl.handle.net/20.500.11754/21467http://dl.acm.org/citation.cfm?doid=2701126.2701205
ISBN
978-145033377-1
DOI
10.1145/2701126.2701205
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE AND ENGINEERING(컴퓨터공학부) > Articles
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