{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:18:34Z","timestamp":1776334714843,"version":"3.51.2"},"reference-count":42,"publisher":"Tech Science Press","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063498","type":"journal-article","created":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T04:13:06Z","timestamp":1745208786000},"page":"4315-4328","source":"Crossref","is-referenced-by-count":3,"title":["Using Outlier Detection to Identify Grey-Sheep Users in Recommender Systems: A Comparative Study"],"prefix":"10.32604","volume":"83","author":[{"given":"Yong","family":"Zheng","sequence":"first","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","unstructured":"Nikolakopoulos AN, Ning X, Desrosiers C, Karypis G. Trust your neighbors: a comprehensive survey of neighborhood-based methods for recommender systems. In: Ricci F, Rokach L, Shapira B, editors. Recommender systems handbook. New York, NY, USA: Springer; 2021. p. 39\u201389.","DOI":"10.1007\/978-1-0716-2197-4_2"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"6087","DOI":"10.1080\/03772063.2021.1997357","article-title":"Matrix factorization in recommender systems: algorithms, applications, and peculiar challenges","volume":"69","author":"Isinkaye","year":"2023","journal-title":"IETE J Res"},{"key":"ref3","series-title":"Proceedings of the 14th ACM Conference on Recommender Systems","first-page":"240","article-title":"Neural collaborative filtering vs. matrix factorization revisited","author":"Rendle","year":"2020"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s13278-020-0626-2","article-title":"A systematic literature review of sparsity issues in recommender systems","volume":"10","author":"Idrissi","year":"2020","journal-title":"Soc Netw Anal Min"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1007\/s10844-022-00698-5","article-title":"Approaches and algorithms to mitigate cold start problems in recommender systems: a systematic literature review","volume":"59","author":"Panda","year":"2022","journal-title":"J Intell Inf Syst"},{"key":"ref6","series-title":"Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization","first-page":"17","article-title":"Identifying grey sheep users in collaborative filtering: a distribution-based technique","author":"Gras","year":"2016"},{"key":"ref7","series-title":"Proceedings of the 6th ACM Conference on Research in Information Technology","article-title":"Identifying grey sheep users by the distribution of user similarities in collaborative filtering","author":"Zheng","year":"2017"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"114061","DOI":"10.1016\/j.eswa.2020.114061","article-title":"Catering for unique tastes: targeting grey-sheep users recommender systems through one-class machine learning","volume":"166","author":"Alabdulrahman","year":"2021","journal-title":"Expert Syst Appl"},{"key":"ref9","series-title":"International Conference on Advanced Information Networking and Applications","first-page":"62","article-title":"An empirical comparison of outlier detection methods for identifying grey-sheep users in recommender systems","author":"Zheng","year":"2024"},{"key":"ref10","series-title":"Proceedings of the 2011 International Conference on Information Systems and Computational Intelligence","first-page":"18","article-title":"Fulfilling the needs of gray-sheep users in recommender systems, a clustering solution","author":"Ghazanfar","year":"2011"},{"key":"ref11","first-page":"228","article-title":"Hybrid recommender for condensed sinhala news with grey sheep user identification","author":"Tennakoon","journal-title":"2020 2nd International Conference on Advancements in Computing (ICAC)"},{"key":"ref12","first-page":"1","article-title":"Outlier detection: methods, models, and classification","volume":"53","author":"Boukerche","year":"2020","journal-title":"ACM Comput Surv"},{"key":"ref13","series-title":"Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work","first-page":"175","article-title":"GroupLens: an open architecture for collaborative filtering of netnews","author":"Resnick","year":"1994"},{"key":"ref14","series-title":"Proceedings of the 10th International Conference on World Wide Web","first-page":"285","article-title":"Item-based collaborative filtering recommendation algorithms","author":"Sarwar","year":"2001"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MC.2009.263","article-title":"Matrix factorization techniques for recommender systems","volume":"42","author":"Koren","year":"2009","journal-title":"Computer"},{"key":"ref16","series-title":"Proceedings of the 26th International Conference on World Wide Web","first-page":"173","article-title":"Neural collaborative filtering","author":"He","year":"2017"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"2457","DOI":"10.1007\/s10115-022-01709-1","article-title":"Graph attention-based collaborative filtering for user-specific recommender system using knowledge graph and deep neural networks","volume":"64","author":"Elahi","year":"2022","journal-title":"Knowl Inf Syst"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3641288","article-title":"Knowledge graph enhanced contextualized attention-based network for responsible user-specific recommendation","volume":"15","author":"Elahi","year":"2024","journal-title":"ACM Trans Intell Syst Technol"},{"key":"ref19","unstructured":"McCrae J, Piatek A, Langley A. Collaborative filtering. 2004 [cited 2025 Mar 27]. Available from: wwwimperialvioletorg."},{"key":"ref20","series-title":"Proceedings of ACM SIGIR Workshop on Recommender Systems","article-title":"Combining content-based and collaborative filters in an online newspaper","volume":"60","author":"Claypool","year":"1999"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"3261","DOI":"10.1016\/j.eswa.2013.11.010","article-title":"Leveraging clustering approaches to solve the gray-sheep users problem in recommender systems","volume":"41","author":"Ghazanfar","year":"2014","journal-title":"Expert Syst Appl"},{"key":"ref22","series-title":"Proceedings of the Second International Conference on Information Management and Machine Intelligence: ICIMMI 2020","first-page":"211","article-title":"Identification of gray sheep using different clustering algorithms","author":"Kaur","year":"2020"},{"key":"ref23","series-title":"Advanced Data Mining and Applications: 13th International Conference","first-page":"148","article-title":"Identification of grey sheep users by histogram intersection in recommender systems","author":"Zheng","year":"2017"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1145\/335191.335388","volume":"29","author":"Breunig","year":"2000","journal-title":"ACM sigmod record"},{"key":"ref25","first-page":"15","article-title":"Anomaly detection: a survey","volume":"41","author":"Chandola","year":"2009","journal-title":"ACM Comput Sur"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1023\/B:AIRE.0000045502.10941.a9","article-title":"A survey of outlier detection methodologies","volume":"22","author":"Hodge","year":"2004","journal-title":"Artif Intell Rev"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1007\/978-3-319-47578-3_7","article-title":"Supervised outlier detection","author":"Aggarwal","year":"2017","journal-title":"Outlier Analysis"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1007\/s10618-015-0444-8","article-title":"On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study","volume":"30","author":"Campos","year":"2016","journal-title":"Data Min Knowl Discov"},{"key":"ref29","series-title":"Proceedings of the 2006 ACM Symposium on Applied Computing","first-page":"635","article-title":"Semi-supervised outlier detection","author":"Gao","year":"2006"},{"key":"ref30","first-page":"1","article-title":"PyOD: a python toolbox for scalable outlier detection","volume":"20","author":"Zhao","year":"2019","journal-title":"J Mach Learn Res"},{"key":"ref31","series-title":"European Conference on Principles of Data Mining and Knowledge Discovery","first-page":"15","article-title":"Fast outlier detection in high dimensional spaces","author":"Angiulli","year":"2002"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1162\/089976601750264965","article-title":"Estimating the support of a high-dimensional distribution","volume":"13","author":"Sch\u00f6lkopf","year":"2001","journal-title":"Neural Comput"},{"key":"ref33","series-title":"Proceedings of the IEEE Foundations and New Directions of Data Mining Workshop","first-page":"172","article-title":"A novel anomaly detection scheme based on principal component classifier","author":"Shyu","year":"2003"},{"key":"ref34","series-title":"Outlier analysis","author":"Aggarwal","year":"2017","journal-title":"An introduction to outlier analysis"},{"key":"ref35","series-title":"2008 Eighth IEEE International Conference on Data Mining","first-page":"413","article-title":"Isolation forest","author":"Liu","year":"2008"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s40558-014-0010-z","article-title":"Leveraging multi-criteria customer feedback for satisfaction analysis and improved recommendations","volume":"14","author":"Jannach","year":"2014","journal-title":"Inf Technol Tour"},{"key":"ref37","series-title":"Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"444","article-title":"Angle-based outlier detection in high-dimensional data","author":"Kriegel","year":"2008"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"1641","DOI":"10.1016\/S0167-8655(03)00003-5","article-title":"Discovering cluster-based local outliers","volume":"24","author":"He","year":"2003","journal-title":"Pattern Recognit Lett"},{"key":"ref39","first-page":"59","article-title":"Histogram-based outlier score (HBOS): a fast unsupervised anomaly detection algorithm","volume":"1","author":"Goldstein","year":"2012","journal-title":"KI-2012: Poster Demo Track"},{"key":"ref40","series-title":"Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data","first-page":"427","article-title":"Efficient algorithms for mining outliers from large data sets","author":"Ramaswamy","year":"2000"},{"key":"ref41","first-page":"6737","article-title":"Unifying local outlier detection methods via graph neural networks","volume":"36","author":"Goodge","year":"2022","journal-title":"Proc of the AAAI Conf Artif Intell"},{"key":"ref42","series-title":"Proceedings of the 2019 SIAM International Conference on Data Mining","first-page":"585","article-title":"LSCP: locally selective combination in parallel outlier ensembles","author":"Zhao"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-3\/TSP_CMC_63498\/TSP_CMC_63498.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:29:29Z","timestamp":1763342969000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n3\/61048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":42,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063498","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}