{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T16:00:56Z","timestamp":1774281656848,"version":"3.50.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2015,1,17]],"date-time":"2015-01-17T00:00:00Z","timestamp":1421452800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Data Min Knowl Disc"],"published-print":{"date-parts":[[2015,9]]},"DOI":"10.1007\/s10618-014-0398-2","type":"journal-article","created":{"date-parts":[[2015,1,16]],"date-time":"2015-01-16T06:40:04Z","timestamp":1421390404000},"page":"1116-1151","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Mining outlying aspects on numeric data"],"prefix":"10.1007","volume":"29","author":[{"given":"Lei","family":"Duan","sequence":"first","affiliation":[]},{"given":"Guanting","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Pei","sequence":"additional","affiliation":[]},{"given":"James","family":"Bailey","sequence":"additional","affiliation":[]},{"given":"Akiko","family":"Campbell","sequence":"additional","affiliation":[]},{"given":"Changjie","family":"Tang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,1,17]]},"reference":[{"key":"398_CR1","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4614-6396-2_1","volume-title":"An introduction to outlier analysis","author":"CC Aggarwal","year":"2013","unstructured":"Aggarwal CC (2013) An introduction to outlier analysis. Springer, New York"},{"key":"398_CR2","doi-asserted-by":"crossref","unstructured":"Aggarwal CC, Yu PS (2001) Outlier detection for high dimensional data. ACM Sigmod Record, ACM, vol 30, pp 37\u201346","DOI":"10.1145\/376284.375668"},{"key":"398_CR3","unstructured":"Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceedings of the 20th international conference on very large data bases, VLDB \u201994, pp 487\u2013499"},{"issue":"1","key":"398_CR4","doi-asserted-by":"crossref","first-page":"7:1","DOI":"10.1145\/1508857.1508864","volume":"34","author":"F Angiulli","year":"2009","unstructured":"Angiulli F, Fassetti F, Palopoli L (2009) Detecting outlying properties of exceptional objects. ACM Trans Database Syst 34(1):7:1\u20137:62","journal-title":"ACM Trans Database Syst"},{"key":"398_CR5","unstructured":"Angiulli F, Fassetti F, Palopoli L, Manco G (2013) Outlying property detection with numerical attributes. CoRR abs\/1306.3558"},{"key":"398_CR6","unstructured":"Bache K, Lichman M (2013) UCI machine learning repository"},{"key":"398_CR7","doi-asserted-by":"crossref","unstructured":"Bhaduri K, Matthews BL, Giannella CR (2011) Algorithms for speeding up distance-based outlier detection. In: Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201911, pp 859\u2013867","DOI":"10.1145\/2020408.2020554"},{"key":"398_CR8","unstructured":"B\u00f6hm K, Keller F, M\u00fcller E, Nguyen HV, Vreeken J (2013) CMI: an information-theoretic contrast measure for enhancing subspace cluster and outlier detection. In: Proceedings of the 13th SIAM international conference on data mining, SDM \u201913, pp 198\u2013206"},{"key":"398_CR9","doi-asserted-by":"crossref","unstructured":"Breunig MM, Kriegel HP, Ng RT, Sander J (2000) LOF: identifying density-based local outliers. In: Proceedings of the 2000 ACM SIGMOD international conference on management of data, SIGMOD \u201900, pp 93\u2013104","DOI":"10.1145\/342009.335388"},{"issue":"3","key":"398_CR10","doi-asserted-by":"crossref","first-page":"15:1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surv 41(3):15:1\u201315:58","journal-title":"ACM Comput Surv"},{"key":"398_CR11","volume-title":"Data mining: concepts and techniques","author":"J Han","year":"2011","unstructured":"Han J, Kamber M, Pei J (2011) Data mining: concepts and techniques, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco","edition":"3"},{"key":"398_CR12","volume-title":"Smoothing techniques: with implementations in S","author":"W H\u00e4rdle","year":"1990","unstructured":"H\u00e4rdle W (1990) Smoothing techniques: with implementations in S. Springer, New York"},{"key":"398_CR13","series-title":"Springer Series in Statistics","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-17146-8","volume-title":"Nonparametric and semiparametric modelss","author":"W H\u00e4rdle","year":"2004","unstructured":"H\u00e4rdle W, Werwatz A, M\u00fcller M, Sperlich S (2004) Nonparametric and semiparametric modelss., Springer Series in StatisticsSpringer, Berlin"},{"issue":"1","key":"398_CR14","doi-asserted-by":"crossref","first-page":"103","DOI":"10.2298\/CSIS0501103H","volume":"2","author":"Z He","year":"2005","unstructured":"He Z, Xu X, Huang ZJ, Deng S (2005) FP-outlier: frequent pattern based outlier detection. Comput Sci Inf Syst\/ComSIS 2(1):103\u2013118","journal-title":"Comput Sci Inf Syst\/ComSIS"},{"key":"398_CR15","doi-asserted-by":"crossref","unstructured":"Keller F, M\u00fcller E, B\u00f6hm K (2012) HiCS: high contrast subspaces for density-based outlier ranking. In: Proceedings of the 28th international conference on data engineering, ICDE \u201912, pp 1037\u20131048","DOI":"10.1109\/ICDE.2012.88"},{"key":"398_CR16","unstructured":"Knorr EM, Ng RT (1999) Finding intensional knowledge of distance-based outliers. In: Proceedings of the 25th international conference on very large data bases, VLDB \u201999, pp 211\u2013222"},{"key":"398_CR17","doi-asserted-by":"crossref","unstructured":"Kriegel HP, Schubert M, Zimek A (2008) Angle-based outlier detection in high-dimensional data. In: Proceedings of the 14th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201908, pp 444\u2013452","DOI":"10.1145\/1401890.1401946"},{"key":"398_CR18","doi-asserted-by":"crossref","unstructured":"Kriegel HP, Kr\u00f6ger P, Schubert E, Zimek A (2009) Outlier detection in axis-parallel subspaces of high dimensional data. In: Proceedings of the 13th Pacific-Asia conference on advances in knowledge discovery and data mining, PAKDD \u201909, pp 831\u2013838","DOI":"10.1007\/978-3-642-01307-2_86"},{"key":"398_CR19","doi-asserted-by":"crossref","unstructured":"M\u00fcller E, Schiffer M, Seidl T (2011) Statistical selection of relevant subspace projections for outlier ranking. In: Proceedings of the 27th IEEE international conference on data engineering, ICDE \u201911, pp 434\u2013445","DOI":"10.1109\/ICDE.2011.5767916"},{"key":"398_CR20","doi-asserted-by":"crossref","unstructured":"M\u00fcller E, Assent I, Iglesias P, M\u00fclle Y, B\u00f6hm K (2012a) Outlier ranking via subspace analysis in multiple views of the data. In: Proceedings of the 12th IEEE international conference on data mining, ICDM \u201912, pp 529\u2013538","DOI":"10.1109\/ICDM.2012.112"},{"key":"398_CR21","doi-asserted-by":"crossref","unstructured":"M\u00fcller E, Keller F, Blanc S, B\u00f6hm K (2012b) OutRules: a framework for outlier descriptions in multiple context spaces. In: ECML\/PKDD (2), pp 828\u2013832","DOI":"10.1007\/978-3-642-33486-3_57"},{"key":"398_CR22","doi-asserted-by":"crossref","unstructured":"Paravastu R, Kumar H, Pudi V (2008) Uniqueness mining. In: Proceedings of the 13th international conference on database systems for advanced applications, DASFAA \u201908, pp 84\u201394","DOI":"10.1007\/978-3-540-78568-2_9"},{"key":"398_CR23","doi-asserted-by":"crossref","unstructured":"Ramaswamy S, Rastogi R, Shim K (2000) Efficient algorithms for mining outliers from large data sets. In: Proceedings of the 2000 ACM SIGMOD international conference on management of data, SIGMOD \u201900, pp 427\u2013438","DOI":"10.1145\/342009.335437"},{"key":"398_CR24","unstructured":"Rymon R (1992) Search through systematic set enumeration. In: Proceedings of the 3rd international conference on principle of knowledge representation and reasoning, KR \u201992, pp 539\u2013550"},{"key":"398_CR25","series-title":"Wiley Series in Probability and Statistics","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316849","volume-title":"Multivariate density estimation: theory, practice, and visualization","author":"DW Scott","year":"1992","unstructured":"Scott DW (1992) Multivariate density estimation: theory, practice, and visualization., Wiley Series in Probability and StatisticsWiley, New York"},{"key":"398_CR26","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-3324-9","volume-title":"Density estimation for statistics and data analysis","author":"BW Silverman","year":"1986","unstructured":"Silverman BW (1986) Density estimation for statistics and data analysis. Chapman and Hall\/CRC, London"},{"key":"398_CR27","doi-asserted-by":"crossref","unstructured":"Tang G, Bailey J, Pei J, Dong G (2013) Mining multidimensional contextual outliers from categorical relational data. In: Proceedings of the 25th international conference on scientific and statistical database management, SSDBM \u201913, pp 43:1\u201343:4","DOI":"10.1145\/2484838.2484883"},{"issue":"5","key":"398_CR28","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1002\/sam.11161","volume":"5","author":"A Zimek","year":"2012","unstructured":"Zimek A, Schubert E, Kriegel HP (2012) A survey on unsupervised outlier detection in high-dimensional numerical data. Stat Anal Data Min 5(5):363\u2013387","journal-title":"Stat Anal Data Min"}],"container-title":["Data Mining and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-014-0398-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10618-014-0398-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-014-0398-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T19:29:46Z","timestamp":1559244586000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10618-014-0398-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,1,17]]},"references-count":28,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2015,9]]}},"alternative-id":["398"],"URL":"https:\/\/doi.org\/10.1007\/s10618-014-0398-2","relation":{},"ISSN":["1384-5810","1573-756X"],"issn-type":[{"value":"1384-5810","type":"print"},{"value":"1573-756X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1,17]]}}}