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1 Ergebnisse
1
ACIRS : A Comprehensive Item Based Clustering Approach t..:
, In:
Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence
,
Hasan, Mahamudul
;
Lubna, Farzana Aktar
;
Chowdhury, Sadia
.. - p. 259-263 , 2019
Link:
https://dl.acm.org/doi/10.1145/3330482.3330526
RT T1 <cTitle>Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence</cTitle>: T1 <Title>ACIRS : A Comprehensive Item Based Clustering Approach to Recommend Appropriate Items in Recommender System</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3330526&Exemplar=1&LAN=DE A1 Hasan, Mahamudul A1 Lubna, Farzana Aktar A1 Chowdhury, Sadia A1 Haque, Nusrat Jarin A1 Omi, Towsif Ahmed PB ACM YR 2019 K1 Clustering Algorithms K1 Item-Item based Collaborative Filtering K1 Recommender System K1 Similarity Metrics K1 Information systems K1 Information retrieval K1 Retrieval models and ranking K1 Similarity measures K1 Retrieval tasks and goals K1 Clustering and classification K1 Recommender systems SP 259 OP 263 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3330482.3330526 DO https://dl.acm.org/doi/10.1145/3330482.3330526 SF ELIB - SuUB Bremen
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