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pro vyhledávání: '"Soojung Lee"'
Autor:
Soojung Lee
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 13:4189-4206
Memory-based collaborative filtering constitutes an important technique of recommender systems mainly due to its simplicity and efficiency. However, it suffers from several fundamentally critical problems when its system makes recommendations based o
Autor:
Soojung Lee
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 11:363-374
Collaborative filtering has been successfully implemented in many commercial recommender systems. These systems recommend items favored by other users with similar preference history to the current user. As finding similar users is critical to the pe
Autor:
Soojung Lee
Publikováno v:
Journal of Creative Information Culture. 4:221-230
Autor:
Soojung Lee
Publikováno v:
Advanced Science Letters. 23:4106-4109
Autor:
Soojung Lee
Publikováno v:
Journal of the Korea Society of Computer and Information. 21:121-126
Autor:
Soojung Lee
Publikováno v:
Data Mining and Big Data ISBN: 9789813295629
DMBD
DMBD
Recommender systems have been essential these days to assist online customers to acquire useful information. However, one of the popular types of the systems called memory-based collaborative filtering suffers from several fundamental problems in spi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57e75dc72d74fafae4c7c7db7d1eee66
https://doi.org/10.1007/978-981-32-9563-6_16
https://doi.org/10.1007/978-981-32-9563-6_16
Autor:
Soojung Lee
Publikováno v:
EECS
Collaborative filtering has been a representative technique for recommender systems. Performance of this technique largely relies on its underlying similarity measure which computes similarity using the user rating records. This paper deals with one
Autor:
Soojung Lee
Publikováno v:
Journal of KIISE. 42:1380-1385
Collaborative filtering is one of the most successfully used methods for recommender systems and has been utilized in various areas such as books and music. The key point of this method is selecting the most proper recommenders, for which various sim
Autor:
Soojung Lee
Publikováno v:
2018 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO).
Collaborative filtering has been a successful technique used by many commercial recommender systems. One of the critical factors affecting the performance of these systems is the similarity measure. Various methods have been developed for similarity
Autor:
Soojung Lee
Publikováno v:
Data Mining and Big Data ISBN: 9783319938028
DMBD
DMBD
Collaborative filtering is a successfully utilized technique in many online commercial recommender systems. Similarity measures play an important role in this technique, as items preferred by similar users are to be recommended. Although various simi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74ebef1fede27f1464cae1a407874978
https://doi.org/10.1007/978-3-319-93803-5_12
https://doi.org/10.1007/978-3-319-93803-5_12