- 요약
- Abstract
- 1. 서론
- 2. 선행 지식
- 3. 실험 설계
http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
https://www.riss.kr/link?id=A107414198
2021
Korean
569
KCI우수등재
학술저널
575-583(9쪽)
0
0
상세조회0
다운로드목차 (Table of Contents)
참고문헌 (Reference)
1 김현진, "효과적인 협업 필터링을 위한 평점 정보 도움을 받는잡음제거 오토인코더" 한국통신학회 43 (43): 1357-1367, 2018
2 박동민, "오토 인코더 기반 추천 시스템을 위한 잠재 표현 학습 방법" 한국정보과학회 47 (47): 207-215, 2020
3 D. Liang, "Variational autoencoders for collaborative filtering" 689-698, 2018
4 Y. Saito, "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback" 501-509, 2020
5 Y. Pana, "Trust-aware collaborative denoising auto-encoder for top-n recommendation"
6 DM. Hawkins, "The problem of overfitting" 1-12, 2003
7 JB. Schafer, "The adaptive web" 291-324, 2007
8 R. Pan, "One-class collaborative filtering" 502-511, 2008
9 N. Hurley, "Novelty and Diversity in Top-N recommendation Analysis and Evaluation" 1-30, 2011
10 AMJ. Schakel, "Measuring word significance using distributed representations of words"
1 김현진, "효과적인 협업 필터링을 위한 평점 정보 도움을 받는잡음제거 오토인코더" 한국통신학회 43 (43): 1357-1367, 2018
2 박동민, "오토 인코더 기반 추천 시스템을 위한 잠재 표현 학습 방법" 한국정보과학회 47 (47): 207-215, 2020
3 D. Liang, "Variational autoencoders for collaborative filtering" 689-698, 2018
4 Y. Saito, "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback" 501-509, 2020
5 Y. Pana, "Trust-aware collaborative denoising auto-encoder for top-n recommendation"
6 DM. Hawkins, "The problem of overfitting" 1-12, 2003
7 JB. Schafer, "The adaptive web" 291-324, 2007
8 R. Pan, "One-class collaborative filtering" 502-511, 2008
9 N. Hurley, "Novelty and Diversity in Top-N recommendation Analysis and Evaluation" 1-30, 2011
10 AMJ. Schakel, "Measuring word significance using distributed representations of words"
11 Y. Koren, "Matrix factorization techniques for recommender systems" 42 : 30-37, 2009
12 H. Steck, "Item popularity and recommendation accuracy" 125-132, 2011
13 E. Brynjolfsson, "Goodbye pareto principle, hello long tail: The effect of search costs on the concentration of product sales" 1373-1386, 2011
14 P. Vincent, "Extracting and composing robust features with denoising autoencoders" 1096-1103, 2008
15 N. Srivastava, "Dropout: a simple way to prevent neural networks from overfitting" 1929-1958, 2014
16 Y. Wu, "Collaborative denoising auto-encoders for top-n recommender systems" 153-162, 2016
17 S. Rendle, "BPR:Bayesian personalized ranking from implicit feedback"
18 S. Sedhain, "Autorec: Autoencoders meet collaborative filtering" 111-112, 2015
19 DP. Kingma, "Adam: A method for stochastic optimization"
20 G. Zhang, "A survey of autoencoder-based recommender systems" 1-21, 2020
21 H. Robbins, "A stochastic approximation method" 400-407, 1951
Predicting the Cache Performance Benefits for In-memory Data Analytics Frameworks
Stochastic Response Time Analysis for Autonomous Vehicle Computing Systems
2-Phase Passage Re-ranking Model based on Neural-Symbolic Ranking Models
Number Normalization in Korean Using the Transformer Model
학술지 이력
연월일 | 이력구분 | 이력상세 | 등재구분 |
---|---|---|---|
2021 | 평가예정 | 계속평가 신청대상 (등재유지) | |
2016-01-01 | 평가 | 우수등재학술지 선정 (계속평가) | |
2015-01-01 | 평가 | 등재학술지 유지 (등재유지) | |
2002-01-01 | 평가 | 학술지 통합 (등재유지) |
학술지 인용정보
기준연도 | WOS-KCI 통합IF(2년) | KCIF(2년) | KCIF(3년) |
---|---|---|---|
2016 | 0.19 | 0.19 | 0.19 |
KCIF(4년) | KCIF(5년) | 중심성지수(3년) | 즉시성지수 |
0.2 | 0.18 | 0.373 | 0.07 |