{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T08:09:37Z","timestamp":1759133377194},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2010,12,8]],"date-time":"2010-12-08T00:00:00Z","timestamp":1291766400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2011,12]]},"DOI":"10.1007\/s10115-010-0343-7","type":"journal-article","created":{"date-parts":[[2010,12,7]],"date-time":"2010-12-07T09:07:08Z","timestamp":1291712828000},"page":"697-725","source":"Crossref","is-referenced-by-count":25,"title":["Non-derivable itemsets for fast outlier detection in large high-dimensional categorical data"],"prefix":"10.1007","volume":"29","author":[{"given":"Anna","family":"Koufakou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jimmy","family":"Secretan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Georgiopoulos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,12,8]]},"reference":[{"issue":"2","key":"343_CR1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1145\/376284.375668","volume":"30","author":"C Aggarwal","year":"2001","unstructured":"Aggarwal C, Yu P (2001) Outlier detection for high dimensional data. ACM SIGMOD Record 30(2): 37\u201346","journal-title":"ACM SIGMOD Record"},{"key":"343_CR2","unstructured":"Agrawal R, Srikant R (1994) Fast algorithms for mining association rules in large databases. In: Proceedings int\u2019l conference on very large data bases, pp 487\u2013499"},{"key":"343_CR3","volume-title":"Outliers in statistical data","author":"V Barnett","year":"1978","unstructured":"Barnett V (1978) Outliers in statistical data. John Wiley and Sons, New York"},{"key":"343_CR4","doi-asserted-by":"crossref","unstructured":"Bay S, Schwabacher M (2003) Mining distance-based outliers in near linear time with randomization and a simple pruning rule. In: Proceedings ACM SIGKDD int\u2019l conference on knowledge discovery and data mining, pp 29\u201338","DOI":"10.1145\/956750.956758"},{"key":"343_CR5","unstructured":"Blake C, Merz C (1998) UCI Repository of machine learning databases. http:\/\/archive.ics.uci.edu (Accessed Sep 2008)"},{"issue":"1","key":"343_CR6","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s10115-009-0212-4","volume":"21","author":"M Boley","year":"2009","unstructured":"Boley M, Grosskreutz H (2009) Approximating the number of frequent sets in dense data. Knowl Inf Syst 21(1): 65\u201389","journal-title":"Knowl Inf Syst"},{"issue":"2","key":"343_CR7","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1145\/335191.335388","volume":"29","author":"M Breunig","year":"2000","unstructured":"Breunig M, Kriegel H, Ng R, Sander J (2000) LOF: identifying density-based local outliers. ACM SIGMOD Record 29(2): 93\u2013104","journal-title":"ACM SIGMOD Record"},{"issue":"1","key":"343_CR8","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/s10618-006-0054-6","volume":"14","author":"T Calders","year":"2007","unstructured":"Calders T, Goethals B (2007) Non-derivable itemset mining. Data Min Knowl Discov 14(1): 171\u2013206","journal-title":"Data Min Knowl Discov"},{"key":"343_CR9","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1007\/11615576_4","volume":"3848","author":"T Calders","year":"2004","unstructured":"Calders T, Rigotti C, Boulicaut J (2004) A survey on condensed representations for frequent sets. LNCS Constraint-Based Min Inductive Databases 3848: 64\u201380","journal-title":"LNCS Constraint-Based Min Inductive Databases"},{"key":"343_CR10","unstructured":"Dokas P, Ertoz L, Kumar V, Lazarevic A, Srivastava J, Tan P (2002) Data mining for network intrusion detection. In: Proceedings NSF workshop on next generation data mining, pp 21\u201330"},{"issue":"1","key":"343_CR11","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s10115-008-0145-3","volume":"19","author":"H Fan","year":"2009","unstructured":"Fan H, Zaiane O, Foss A, Wu J (2009) Resolution-based outlier factor: detecting the top-n most outlying data points in engineering data. Knowl Inf Syst 19(1): 31\u201351","journal-title":"Knowl Inf Syst"},{"key":"343_CR12","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-59830-2","volume-title":"Formal concept analysis","author":"B Ganter","year":"1999","unstructured":"Ganter B, Wille R (1999) Formal concept analysis. Springer, Berlin"},{"key":"343_CR13","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-015-3994-4","volume-title":"Identification of outliers","author":"D Hawkins","year":"1980","unstructured":"Hawkins D (1980) Identification of outliers. Chapman and Hall, London"},{"key":"343_CR14","unstructured":"Hays C (2004) What Wal-Mart knows about customers habits. The New York Times"},{"key":"343_CR15","doi-asserted-by":"crossref","unstructured":"He Z, Deng S, Xu X, Huang J (2006) A fast greedy algorithm for outlier mining. In: Proceedings Pacific-Asia conference on knowledge and data discovery, pp 567\u2013576","DOI":"10.1007\/11731139_67"},{"issue":"1","key":"343_CR16","doi-asserted-by":"crossref","first-page":"103","DOI":"10.2298\/CSIS0501103H","volume":"2","author":"Z He","year":"2005","unstructured":"He Z, Xu X, Huang J, Deng S (2005) FP-Outlier: frequent pattern based outlier detection. Comp Sci Inf Syst 2(1): 103\u2013118","journal-title":"Comp Sci Inf Syst"},{"issue":"1","key":"343_CR17","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.datak.2007.10.003","volume":"65","author":"K Jea","year":"2008","unstructured":"Jea K, Chang M (2008) Discovering frequent itemsets by support approximation and itemset clustering. Data Knowl Eng 65(1): 90\u2013107","journal-title":"Data Knowl Eng"},{"issue":"3","key":"343_CR18","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s007780050006","volume":"8","author":"E Knorr","year":"2000","unstructured":"Knorr E, Ng R, Tucakov V (2000) Distance-based outliers: algorithms and applications. Int\u2019l J Very Large Data Bases VLDB 8(3): 237\u2013253","journal-title":"Int\u2019l J Very Large Data Bases VLDB"},{"issue":"2","key":"343_CR19","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s10618-009-0148-z","volume":"20","author":"A Koufakou","year":"2010","unstructured":"Koufakou A, Georgiopoulos M (2010) A fast outlier detection strategy for distributed high-dimensional data sets with mixed attributes. Data Min Knowl Discov 20(2): 259\u2013289","journal-title":"Data Min Knowl Discov"},{"key":"343_CR20","unstructured":"Koufakou A, Georgiopoulos M, Anagnostopoulos G (2008) Detecting outliers in high-dimensional datasets with mixed attributes. In: Int\u2019l conference on data mining DMIN, pp 427\u2013433"},{"key":"343_CR21","doi-asserted-by":"crossref","unstructured":"Koufakou A, Ortiz E, Georgiopoulos M, Anagnostopoulos G, Reynolds K (2007) A scalable and efficient outlier detection strategy for categorical data. In: IEEE int\u2019l conference on tools with artificial intelligence ICTAI, pp 210\u2013217","DOI":"10.1109\/ICTAI.2007.125"},{"issue":"2","key":"343_CR22","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s10618-005-0014-6","volume":"12","author":"M Otey","year":"2006","unstructured":"Otey M, Ghoting A, Parthasarathy S (2006) Fast distributed outlier detection in mixed-attribute data sets. Data Min Knowl Discov 12(2): 203\u2013228","journal-title":"Data Min Knowl Discov"},{"key":"343_CR23","doi-asserted-by":"crossref","unstructured":"Pasquier N., Bastide Y, Taouil R, Lakhal L (1999) Discovering frequent closed itemsets for association rules. In: Proceedings 7th Int\u2019l conference on database theory ICDT, pp 398\u2013416","DOI":"10.1007\/3-540-49257-7_25"},{"issue":"1","key":"343_CR24","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1023\/B:MACH.0000008084.60811.49","volume":"54","author":"D Tax","year":"2004","unstructured":"Tax D, Duin R (2004) Support vector data description. Mach Learn 54(1): 45\u201366","journal-title":"Mach Learn"},{"issue":"1","key":"343_CR25","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10115-005-0216-7","volume":"9","author":"J Wang","year":"2006","unstructured":"Wang J, Karypis G (2006) On efficiently summarizing categorical databases. Knowl Inf Syst 9(1): 19\u201337","journal-title":"Knowl Inf Syst"},{"issue":"1","key":"343_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10115-007-0114-2","volume":"14","author":"X Wu","year":"2008","unstructured":"Wu X, Kumar V, Ross Quinlan J, Ghosh J, Yang Q, Motoda H, McLachlan G, Ng A, Liu B, Yu P, Zhou Z, Steinbach M, Hand D, Steinberg D (2008) Top 10 algorithms in data mining. Knowl Inf Syst 14(1): 1\u201337","journal-title":"Knowl Inf Syst"},{"issue":"3","key":"343_CR27","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1109\/TKDE.2006.46","volume":"18","author":"H Xiong","year":"2006","unstructured":"Xiong H, Pandey G, Steinbach M, Kumar V (2006) Enhancing data analysis with noise removal. IEEE Trans Knowl Data Eng 18(3): 304\u2013319","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"343_CR28","unstructured":"Yang X, Wang Z, Bing L, Shouzhi Z, Wei W, Bole S (2005) Non-almost-derivable frequent itemsets mining. In: Proceedings int\u2019l conference on computer and information technology, pp 157\u2013161"},{"issue":"2","key":"343_CR29","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10115-008-0131-9","volume":"17","author":"D Yankov","year":"2008","unstructured":"Yankov D, Keogh E, Rebbapragada U (2008) Disk aware discord discovery: finding unusual time series in terabyte sized datasets. Knowl Inf Syst 17(2): 241\u2013262","journal-title":"Knowl Inf Syst"},{"issue":"4","key":"343_CR30","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1109\/TKDE.2005.60","volume":"17","author":"M Zaki","year":"2005","unstructured":"Zaki M, Hsiao C (2005) Efficient algorithms for mining closed itemsets and their lattice structure. IEEE Trans Knowl Data Eng 17(4): 462\u2013478","journal-title":"IEEE Trans Knowl Data Eng"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-010-0343-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-010-0343-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-010-0343-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,6]],"date-time":"2019-06-06T17:49:27Z","timestamp":1559843367000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-010-0343-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,12,8]]},"references-count":30,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2011,12]]}},"alternative-id":["343"],"URL":"https:\/\/doi.org\/10.1007\/s10115-010-0343-7","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,12,8]]}}}