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1 F. Hao, "k-cliques mining in dynamic social networks based on triadic formal concept analysis" 209 : 57-66, 2016
2 F. Hao, "When social computing meets soft computing : opportunities and insights" 8 : 8-, 2018
3 G. Palla, "Uncovering the overlapping community structure of complex networks in nature and society" 435 (435): 814-818, 2005
4 F. M. Harper, "The MovieLens Datasets : history and context" 5 (5): 2015
5 Fei Hao, "Similarity Evalution between Graphs: A Formal Concept Analysis Approach" 한국정보처리학회 13 (13): 1158-1167, 2017
6 J. M. Kumpula, "Sequential algorithm for fast clique percolation" 78 (78): 2008
7 F. Ricci, "Recommender Systems Handbook" Springer 1-35, 2011
8 이다니엘, "Personalizing Information Using Users’ Online Social Networks: A Case Study of CiteULike" 한국정보처리학회 11 (11): 1-21, 2015
9 A. Souril, "Personality classification based on profiles of social networks’ users and the five-factor model of personality" 8 : 24-, 2018
10 정운해, "Performance Improvement of a Movie Recommendation System based on Personal Propensity and Secure Collaborative Filtering" 한국정보처리학회 9 (9): 157-172, 2013
11 E. Gregori, "Parallel(k)-clique community detection on large-scale networks" 24 (24): 1651-1660, 2013
12 F. Hao, "K-clique communities detection in social networks based on formal concept analysis" 11 (11): 250-259, 2017
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17 P. Jomsri, "Book recommendation system for digital library based on user profiles by using association rule" 130-134, 2014
18 A. S. Tewari, "Book recommendation system based on collaborative filtering and association rule mining for college students" 135-138, 2014
19 C. W. K. Leung, "Applying cross-level association rule mining to cold-start recommendations" 133-136, 2007
20 R. J. Hyndman, "Another look at measures of forecast accuracy" 22 (22): 679-688, 2006
21 P. Vilakone, "An efficient movie recommendation algorithm based on improved k-clique" 8 : 38-, 2018
22 S. Kim, "A new metric of absolute percentage error for intermittent demand forecasts" 32 (32): 669-679, 2016
23 H. Jafarkarimi, "A naïve recommendation model for large databases" 2 (2): 216-219, 2012
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