{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T02:25:31Z","timestamp":1768703131093,"version":"3.49.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T00:00:00Z","timestamp":1516147200000},"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":["Knowl Inf Syst"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s10115-017-1148-8","type":"journal-article","created":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T13:55:06Z","timestamp":1516197306000},"page":"691-715","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Subspace histograms for outlier detection in linear time"],"prefix":"10.1007","volume":"56","author":[{"given":"Saket","family":"Sathe","sequence":"first","affiliation":[]},{"given":"Charu C.","family":"Aggarwal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,1,17]]},"reference":[{"key":"1148_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47578-3","volume-title":"Outlier analysis","author":"C Aggarwal","year":"2017","unstructured":"Aggarwal C (2017) Outlier analysis, 2nd edn. Springer, Berlin","edition":"2"},{"key":"1148_CR2","doi-asserted-by":"crossref","unstructured":"Aggarwal C, Yu P (2001) Outlier detection for high-dimensional data. In: ACM SIGMOD conference","DOI":"10.1145\/375663.375668"},{"key":"1148_CR3","doi-asserted-by":"crossref","unstructured":"Aggarwal C, Zhao Y, Yu P (2011) Outlier detection in graph streams. In: ICDE","DOI":"10.1109\/ICDE.2011.5767885"},{"key":"1148_CR4","doi-asserted-by":"crossref","unstructured":"Aggarwal C, Sathe S (2015) Theoretical foundations and algorithms for outlier ensembles. In: ACM SIGKDD explorations","DOI":"10.1145\/2830544.2830549"},{"key":"1148_CR5","doi-asserted-by":"crossref","unstructured":"Aggarwal C (2013) Outlier ensembles. Position paper. In: ACM SIGKDD explorations","DOI":"10.1145\/2481244.2481252"},{"key":"1148_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-54765-7","volume-title":"Outlier ensembles: an introduction","author":"C Aggarwal","year":"2017","unstructured":"Aggarwal C, Sathe S (2017) Outlier ensembles: an introduction. Springer, Berlin"},{"key":"1148_CR7","unstructured":"Akoglu L, Muller E, Vreeken J (2013) ACM KDD workshop on outlier detection and description"},{"key":"1148_CR8","doi-asserted-by":"crossref","unstructured":"Akoglu L, Tong H, Vreeken J, Faloutsos C (2012) Fast and reliable anomaly detection in categorical data. In: ACM CIKM conference","DOI":"10.1145\/2396761.2396816"},{"key":"1148_CR9","doi-asserted-by":"crossref","unstructured":"Angiulli F, Pizzuti C (2002) Fast outlier detection in high dimensional spaces. In: PKDD conference","DOI":"10.1007\/3-540-45681-3_2"},{"key":"1148_CR10","doi-asserted-by":"crossref","unstructured":"Angiulli F, Fassetti F (2007) Detecting distance-based outliers in streams of data. In: ACM CIKM conference","DOI":"10.1145\/1321440.1321552"},{"key":"1148_CR11","doi-asserted-by":"crossref","unstructured":"Assent I, Kranen P, Beldauf C, Seidl T (2012) AnyOut: anytime outlier detection in streaming data. In: DASFAA conference","DOI":"10.1007\/978-3-642-29038-1_18"},{"key":"1148_CR12","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: KDD","DOI":"10.1145\/956750.956758"},{"key":"1148_CR13","doi-asserted-by":"crossref","unstructured":"Breunig M, Kriegel H-P, Ng R, Sander J (2000) LOF: identifying density-based local outliers. In: SIGMOD","DOI":"10.1145\/342009.335388"},{"key":"1148_CR14","doi-asserted-by":"crossref","unstructured":"Chen J, Sathe S, Aggarwal C, Turaga D (2017) Outlier Detection with Autoencoder Ensembles. In: SDM conference","DOI":"10.1137\/1.9781611974973.11"},{"key":"1148_CR15","doi-asserted-by":"crossref","unstructured":"Cormode G, Muthukrishnan S (2004) An improved data stream summary: the count-min sketch and its applications. In: LATIN","DOI":"10.1007\/978-3-540-24698-5_7"},{"key":"1148_CR16","doi-asserted-by":"crossref","unstructured":"Dang X, Misenkova B, Assent I, and Ng R (2013) Outlier detection with space transformation and spectral analysis. In: SDM conference","DOI":"10.1137\/1.9781611972832.25"},{"key":"1148_CR17","doi-asserted-by":"crossref","unstructured":"Keller F, Muller E, Bohm K (2012) HiCS: high-contrast subspaces for density-based outlier ranking. In: IEEE ICDE conference","DOI":"10.1109\/ICDE.2012.88"},{"key":"1148_CR18","unstructured":"Knorr E, Ng R (1998) Algorithms for mining distance-based outliers in large datasets. In: VLDB conference"},{"key":"1148_CR19","doi-asserted-by":"crossref","unstructured":"Kriegel H-P, Schubert M, Zimek A (2008) Angle-based outlier detection in high-dimensional data. In: KDD","DOI":"10.1145\/1401890.1401946"},{"key":"1148_CR20","doi-asserted-by":"crossref","unstructured":"Lazarevic A, Kumar V (2005) Feature bagging for outlier detection. In: KDD","DOI":"10.1145\/1081870.1081891"},{"key":"1148_CR21","doi-asserted-by":"crossref","unstructured":"Liu FT, Ting KM, Zhou Z-H (2008) Isolation forest. In: ICDM","DOI":"10.1109\/ICDM.2008.17"},{"key":"1148_CR22","doi-asserted-by":"crossref","unstructured":"Muller E, Schiffer M, Seidl T (2011) Statistical selection of relevant subspace projections for outlier ranking. In: ICDE conference","DOI":"10.1109\/ICDE.2011.5767916"},{"key":"1148_CR23","doi-asserted-by":"crossref","unstructured":"Muller E, Assent I, Iglesias P, Mulle Y, Bohm K (2012) Outlier ranking via subspace analysis in multiple views of the data. In: ICDM","DOI":"10.1109\/ICDM.2012.112"},{"key":"1148_CR24","doi-asserted-by":"crossref","unstructured":"Papadimitriou S, Kitagawa H, Gibbons P, Faloutsos C (2003) LOCI: fast outlier detection using the local correlation integral. In: ICDE","DOI":"10.1109\/ICDE.2003.1260802"},{"key":"1148_CR25","doi-asserted-by":"crossref","unstructured":"Pokrajac D, Lazarevic A, Latecki L (2007) Incremental local outlier detection for data streams. In: CIDM conference","DOI":"10.1109\/CIDM.2007.368917"},{"key":"1148_CR26","doi-asserted-by":"crossref","unstructured":"Ramaswamy S, Rastogi R, Shim K (2000) Efficient algorithms for mining outliers from large data sets. In: ACM SIGMOD conference","DOI":"10.1145\/342009.335437"},{"key":"1148_CR27","unstructured":"Sathe S, Aggarwal C (2013) LODES: local density meets spectral outlier detection. In: SDM conference"},{"key":"1148_CR28","doi-asserted-by":"crossref","unstructured":"Sathe S, Aggarwal C (2016) Outlier detection in linear time with randomized hashing. In: ICDM conference","DOI":"10.1109\/ICDM.2016.0057"},{"key":"1148_CR29","unstructured":"Tan SC, Ting KM, Liu TF (2011) Fast anomaly detection for streaming data. In: IJCAI conference"},{"key":"1148_CR30","doi-asserted-by":"crossref","unstructured":"Wu K, Zhang K, Fan W, Edwards A, Yu P (2014) RS-forest: a rapid density estimator for streaming anomaly detection. In: ICDM","DOI":"10.1109\/ICDM.2014.45"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-017-1148-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-017-1148-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-017-1148-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T13:05:27Z","timestamp":1570626327000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-017-1148-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,17]]},"references-count":30,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["1148"],"URL":"https:\/\/doi.org\/10.1007\/s10115-017-1148-8","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1,17]]},"assertion":[{"value":"13 March 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2017","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2017","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 January 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}