A Locality-Sensitive Hashing-based Automatic Group Identification Approach in Group Recommendation-Reference-Cited by-同舟云学术

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A Locality-Sensitive Hashing-based Automatic Group Identification Approach in Group Recommendation

Published:2022-09-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
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Author:

Wang Yuqing¹,Liu Yuwen²,Yang Yihong³,Kong Lingzhen⁴,Miao Ying¹

Affiliation:

1. Qufu Normal University,School of Computer Science,China

2. China University of Petroleum,College of Computer Science and Technology,China

3. China University of Geosciences (Beijing),School of Information Engineering,Beijing,China

4. Nanjing University of Science and Technology,School of Computer Science Engineering,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9927523/9927699/09927950.pdf?arnumber=9927950

Reference19 articles.

1. Groups Identification and Individual Recommendations in Group Recommendation Algorithms;boratto;PRSAT RecSys,2010

2. Using Collaborative Filtering to Overcome the Curse of Dimensionality when Clustering Users in a Group Recommender System;boratto;ICEIS,2014

3. Discovery and representation of the preferences of automatically detected groups: Exploiting the link between group modeling and clustering

4. ART: group recommendation approaches for automatically detected groups

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