{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T04:41:09Z","timestamp":1770525669797,"version":"3.49.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2007,7,12]],"date-time":"2007-07-12T00:00:00Z","timestamp":1184198400000},"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":[[2008,7]]},"DOI":"10.1007\/s10115-007-0092-4","type":"journal-article","created":{"date-parts":[[2007,7,16]],"date-time":"2007-07-16T19:16:22Z","timestamp":1184613382000},"page":"1-27","source":"Crossref","is-referenced-by-count":102,"title":["A survey on algorithms for mining frequent itemsets over data streams"],"prefix":"10.1007","volume":"16","author":[{"given":"James","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiping","family":"Ke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wilfred","family":"Ng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2007,7,12]]},"reference":[{"key":"92_CR1","doi-asserted-by":"crossref","unstructured":"Agrawal R, Imielinski T, Swami A (1993) Mining association rules between sets of items in large databases. In: Buneman P, Jajodia S (eds) Proceedings of the ACM SIGMOD international conference on management of data, Washington DC, pp 207\u2013216","DOI":"10.1145\/170035.170072"},{"key":"92_CR2","unstructured":"Agrawal R, Srikant R (1994) Fast algorithms for mining association rules in large databases. In: Bocca J, Jarke M, Zaniolo C (eds) Proceedings of 20th international conference on very large data bases, Santiago de Chile, Chile, September 1994, pp 487\u2013499"},{"key":"92_CR3","doi-asserted-by":"crossref","unstructured":"Agrawal R, Srikant R (1995) Mining sequential patterns. In: Yu P, Chen A (eds) Proceedings of the eleventh international conference on data engineering, Taipei, Taiwan, March 1995, pp 3\u201314","DOI":"10.1109\/ICDE.1995.380415"},{"key":"92_CR4","doi-asserted-by":"crossref","unstructured":"Babcock B, Babu S, Datar M, Motwani R, Widom J (2002) Models and issues in data stream systems. In: Popa L (eds) Proceedings of the twenty-first ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems, Wisconsin, USA, June 2002, pp 1\u201316","DOI":"10.1145\/543613.543615"},{"issue":"2","key":"92_CR5","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1007\/s10115-005-0201-1","volume":"9","author":"F Bonchi","year":"2005","unstructured":"Bonchi F and Lucchese C (2005). On condensed representations of constrained frequent patterns. Knowl Inf Syst 9(2): 180\u2013201","journal-title":"Knowl Inf Syst"},{"issue":"1","key":"92_CR6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1021571501451","volume":"7","author":"J Boulicaut","year":"2003","unstructured":"Boulicaut J, Bykowski A and Rigotti C (2003). Free-sets: a condensed representation of boolean data for the approximation of frequency queries. Data Min Knowl Discov 7(1): 5\u201322","journal-title":"Data Min Knowl Discov"},{"key":"92_CR7","doi-asserted-by":"crossref","unstructured":"Brin S, Motwani R, Silverstein C (1997) Beyond market basket: generalizing association rules to correlations. In: Peckham J (eds) Proceedings of the ACM SIGMOD international conference on management of data, Arizona, May 1997, pp 265\u2013276","DOI":"10.1145\/253260.253327"},{"key":"92_CR8","doi-asserted-by":"crossref","unstructured":"Calders T, Goethals B (2002) Mining all non-derivable frequent itemsets. In: Elomaa T, Mannila H, Toivonen H (eds) Proceedings of the principles of data mining and knowledge discovery, 6th European conference, Helsinki, Finland, August 2002, pp 74\u201385","DOI":"10.1007\/3-540-45681-3_7"},{"key":"92_CR9","doi-asserted-by":"crossref","unstructured":"Chang JH, Lee WS (2003) Finding recent frequent itemsets adaptively over online data streams. In: Getoor L, Senator T, Domingos P, Faloutsos C (eds) Proceedings of the Ninth ACM SIGKDD international conference on knowledge discovery and data mining, Washington, DC, August 2003, pp 487\u2013492","DOI":"10.1145\/956750.956807"},{"key":"92_CR10","unstructured":"Chang JH, Lee WS (2003) stWin: adaptively monitoring the recent change of frequent itemsets over online data streams. In: Proceedings of the 2003 ACM CIKM international conference on information and knowledge management, New Orleans, Louisiana, USA, November 2003, pp 536\u2013539"},{"issue":"4","key":"92_CR11","first-page":"753","volume":"20","author":"JH Chang","year":"2004","unstructured":"Chang JH and Lee WS (2004). A sliding window method for finding recently frequent itemsets over online data streams. J Inf Sci Eng 20(4): 753\u2013762","journal-title":"J Inf Sci Eng"},{"issue":"1","key":"92_CR12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0304-3975(03)00400-6","volume":"312","author":"M Charikar","year":"2004","unstructured":"Charikar M, Chen K and Farach-Colton M (2004). Finding frequent items in data streams. Theor Comput Sci 312(1): 3\u201315","journal-title":"Theor Comput Sci"},{"key":"92_CR13","doi-asserted-by":"crossref","unstructured":"Chen Y, Dong G, Han J, Wah BW, Wang J (2002) Multi-dimensional regression analysis of time-series data streams. In: Proceedings of the 28th international conference on very large data bases, Hong Kong, August 2002, pp 323\u2013334","DOI":"10.1016\/B978-155860869-6\/50036-6"},{"key":"92_CR14","doi-asserted-by":"crossref","unstructured":"Cheng J, Ke Y, Ng W (2006) Maintaining frequent itemsets over high-speed data streams. In: Ng WK, Kitsuregawa M, Li J, Chang K (eds) Proceedings of the 10th Pacific-asia Conference on knowledge discovery and data mining, Singapore, April 2006, pp 462\u2013467","DOI":"10.1007\/11731139_53"},{"key":"92_CR15","doi-asserted-by":"crossref","unstructured":"Cheng J, Ke Y, Ng W (2006) \u03b4-Tolerance closed frequent itemsets. In: Proceedings of the 6th IEEE international conference on data mining, Singapore, Hong Kong, December 2006, pp 139\u2013148","DOI":"10.1109\/ICDM.2006.1"},{"issue":"4","key":"92_CR16","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1214\/aoms\/1177729330","volume":"23","author":"H Chernoff","year":"1952","unstructured":"Chernoff H (1952). A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Ann Math Stat 23(4): 493\u2013507","journal-title":"Ann Math Stat"},{"key":"92_CR17","unstructured":"Chi Y, Wang H, Yu P, Muntz R (2004) Moment: maintaining closed frequent itemsets over a stream sliding window. In: Proceedings of the 4th IEEE international conference on data mining, Brighton, UK, November 2004, pp 59\u201366"},{"issue":"3","key":"92_CR18","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/s10115-006-0003-0","volume":"10","author":"Y Chi","year":"2006","unstructured":"Chi Y, Wang H, Yu P and Muntz R (2006). Catch the moment: maintaining closed frequent itemsets over a data stream sliding window. Knowl Inf Syst 10(3): 265\u2013294","journal-title":"Knowl Inf Syst"},{"key":"92_CR19","doi-asserted-by":"crossref","unstructured":"Cormode G, Muthukrishnan S (2003) What\u2019s hot and what\u2019s not: tracking most frequent items dynamically. In: Proceedings of the twenty-second ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems, San Diego, June 2003, pp 296\u2013306","DOI":"10.1145\/773153.773182"},{"key":"92_CR20","doi-asserted-by":"crossref","unstructured":"Garofalakis M, Gehrke J, Rastogi R (2002) Querying and mining data streams: you only get one look a tutorial. In: Franklin M, Moon B, Ailamaki A (eds) Proceedings of the 2002 ACM SIGMOD international conference on management of data, Wisconsin, June 2002, pp 635","DOI":"10.1145\/564691.564794"},{"key":"92_CR21","unstructured":"Giannella C, Han J, Pei J, Yan X, Yu P (2004) Mining frequent patterns in data streams at multiple time granularities. In: Kargupta H, Joshi A, Sivakumar D, Yesha Y (eds) Data mining: next generation challenges and future directions, MIT\/AAAI Press, pp 191\u2013212"},{"key":"92_CR22","unstructured":"Goethals B, Zaki M (2003) FIMI \u201903, Frequent itemset mining implementations. In: Proceedings of the ICDM 2003 workshop on frequent itemset mining implementations, December 2003, Melbourne, Florida, USA"},{"issue":"2","key":"92_CR23","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1145\/776985.776986","volume":"32","author":"L Golab","year":"2003","unstructured":"Golab L and \u00d6zsu MT (2003). Issues in data stream management. SIGMOD Rec 32(2): 5\u201314","journal-title":"SIGMOD Rec"},{"key":"92_CR24","doi-asserted-by":"crossref","unstructured":"Gouda K, Zaki M (2001) Efficiently mining maximal frequent itemsets. In: Cercone N, Lin TY, Wu X (eds) Proceedings of the 2001 IEEE international conference on data mining, San Jose, 29 November \u2013 2 December 2001, pp 163\u2013170","DOI":"10.1109\/ICDM.2001.989514"},{"key":"92_CR25","doi-asserted-by":"crossref","unstructured":"Han J, Pei J, Yin Y (2000) Mining frequent patterns without candidate generation. In: Chen W, Naughton J, Bernstein P (eds) Proceedings of the 2000 ACM SIGMOD international conference on management of data, Texas, May 2000, pp 1\u201312","DOI":"10.1145\/342009.335372"},{"key":"92_CR26","doi-asserted-by":"crossref","unstructured":"Hidber C (1999) Online association rule mining. In: Delis A, Faloutsos C, Ghandeharizadeh S (eds) Proceedings of the ACM SIGMOD international conference on management of data, Philadelphia, Pennsylvania, June 1999, pp 145\u2013156","DOI":"10.1145\/304182.304195"},{"key":"92_CR27","doi-asserted-by":"crossref","unstructured":"Jin C, Qian W, Sha C, Yu J, Zhou A (2003) Dynamically maintaining frequent items over a data stream. In: Proceedings of the 2003 ACM CIKM international conference on information and knowledge management, New Orleans, Louisiana, USA, November 2003, pp 287\u2013294","DOI":"10.1145\/956863.956918"},{"key":"92_CR28","unstructured":"Jin R, Agrawal G (2005) An algorithm for in-core frequent itemset mining on streaming data. In: Proceedings of the 5th IEEE international conference on data mining, Houston, Texas, USA, November 2005, pp 210\u2013217"},{"key":"92_CR29","unstructured":"Lee D, Lee W (2005) Finding maximal frequent itemsets over online data streams adaptively. In: Proceedings of the 5th IEEE international conference on data mining, Houston, Texas, USA, November 2005, pp 266\u2013273"},{"key":"92_CR30","doi-asserted-by":"crossref","unstructured":"Lee C, Lin C, Chen M (2001) Sliding-window filtering: an efficient algorithm for incremental mining. In: Proceedings of the 2001 ACM CIKM international conference on information and knowledge management, Atlanta, Georgia, USA, November 2001, pp 263\u2013270","DOI":"10.1145\/502585.502630"},{"key":"92_CR31","unstructured":"Li H, Lee S, Shan M (2004) An efficient algorithm for mining frequent itemsets over the entire history of data streams. In: Proceedings of the first international workshop on knowledge discovery in data streams, in conjunction with the 15th European conference on machine learning ECML and the 8th European conference on the principals and practice of knowledge discovery in databases PKDD, Pisa, Italy, 2004"},{"key":"92_CR32","unstructured":"Liu B, Hsu W, Ma Y (1998) Integrating classification and association rule mining. In: Agrawal R, Stolorz P, Piatetsky-Shapiro G (eds) Proceedings of the fourth international conference on knowledge discovery and data mining, New York, August 1998, pp 80\u201386"},{"key":"92_CR33","doi-asserted-by":"crossref","unstructured":"Manjhi A, Shkapenyuk V, Dhamdhere K , Olston C (2005) Finding (recently) frequent items in distributed data streams. In: Proceedings of the 21st international conference on data engineering, Tokyo, Japan, April 2005, pp 767\u2013778","DOI":"10.1109\/ICDE.2005.68"},{"key":"92_CR34","doi-asserted-by":"crossref","unstructured":"Manku GS, Motwani R (2002) Approximate frequency counts over data streams. In: Proceedings of the 28th international conference on very large data bases, Hong Kong, August 2002, pp 346\u2013357","DOI":"10.1016\/B978-155860869-6\/50038-X"},{"issue":"3","key":"92_CR35","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1023\/A:1009748302351","volume":"1","author":"H Mannila","year":"1997","unstructured":"Mannila H, Toivonen H and Verkamo AI (1997). Discovery of frequent episodes in event sequences. Data Min Knowl Discov 1(3): 259\u2013289","journal-title":"Data Min Knowl Discov"},{"issue":"1","key":"92_CR36","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/TKDE.2003.1161582","volume":"15","author":"E Omiecinski","year":"2003","unstructured":"Omiecinski E (2003). Alternative interest measures for mining associations in databases. IEEE Trans Knowl Data Eng 15(1): 57\u201369","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"92_CR37","doi-asserted-by":"crossref","unstructured":"Pasquier N, Bastide Y, Taouil R, Lakhal L (1999) Discovering frequent closed itemsets for association rules. In: Beeri C, Buneman P (eds) Proceedings of the 7th international conference on database theory, Jerusalem, Israel, January 1999, pp 398\u2013416","DOI":"10.1007\/3-540-49257-7_25"},{"key":"92_CR38","unstructured":"Pavan A, Tirthapura S (2005) Range efficient computation of F0 over massive data streams. In: Proceedings of the 21st international conference on data engineering, Tokyo, Japan, April 2005, pp 32\u201343"},{"issue":"5","key":"92_CR39","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1007\/s10115-003-0133-6","volume":"6","author":"J Pei","year":"2004","unstructured":"Pei J, Dong G, Zou W and Han J (2004). Mining condensed frequent-pattern bases. Knowl Inf Syst 6(5): 570\u2013594","journal-title":"Knowl Inf Syst"},{"key":"92_CR40","doi-asserted-by":"crossref","unstructured":"Srivastava U, Widom J (2004) Memory-limited execution of windowed stream joins. In: Nascimento et\u00a0al. (eds) Proceedings of the thirtieth international conference on very large data bases, Toronto, Canada, August 31 \u2013 September 3 2004, pp 324\u2013335","DOI":"10.1016\/B978-012088469-8.50031-0"},{"key":"92_CR41","unstructured":"Toivonen H (1996) Sampling large databases for association rules. In: Vijayaraman TM, Buchmann A, Mohan C, Sarda N (eds) Proceedings of the 22nd international conference on very large data bases, Mumbai (Bombay), India, September 1996, pp 134\u2013145"},{"key":"92_CR42","doi-asserted-by":"crossref","unstructured":"Wang J, Han J, Pei J (2003) CLOSET\u00a0+\u00a0: searching for the best strategies for mining frequent closed itemsets. In: Getoor L, Senator T, Domingos P, Faloutsos C (eds) Proceedings of the ninth ACM SIGKDD international conference on knowledge discovery and data mining, Washington, DC, August 2003, pp 236\u2013245","DOI":"10.1145\/956750.956779"},{"key":"92_CR43","doi-asserted-by":"crossref","unstructured":"Wang H, Yang J, Wang W, Yu P (2002) Clustering by pattern similarity in large data sets. In: Franklin M, Moon B, Ailamaki A (eds) Proceedings of the 2002 ACM SIGMOD international conference on management of data, Wisconsin, June 2002, pp 394\u2013405","DOI":"10.1145\/564691.564737"},{"key":"92_CR44","unstructured":"Xin D, Han J, Yan X, Cheng H (2005) Mining compressed frequent-pattern sets. In: B\u00d6hm et\u00a0al. (eds) Proceedings of the 31st international conference on very large data bases, Trondheim, Norway, September 2\u2013August 30, 2005, pp 709\u2013720"},{"key":"92_CR45","unstructured":"Yu J, Chong Z, Lu H, Zhou A (2004) False positive or false negative: mining frequent itemsets from high speed transactional data streams. In: Nascimento et\u00a0al. (eds) Proceedings of the thirtieth international conference on very large data bases, Toronto, Canada, September 3\u2013August 31, 2004, pp 204\u2013215"},{"key":"92_CR46","doi-asserted-by":"crossref","unstructured":"Zaki M (2000) Generating non-redundant association rules. In: Proceedings of the ACM SIGKDD international conference on knowledge discovery and data mining, August 2000, pp 34\u201343","DOI":"10.1145\/347090.347101"},{"key":"92_CR47","doi-asserted-by":"crossref","unstructured":"Zaki M, Hsiao CJ (2002) CHARM: an efficient algorithm for closed itemset mining. In: Grossman et\u00a0al. (eds) Proceedings of the second SIAM international conference on data mining, Arlington, VA, USA, April 2002","DOI":"10.1137\/1.9781611972726.27"},{"key":"92_CR48","doi-asserted-by":"crossref","unstructured":"Zaki M, Parthasarathy S, Li W, Ogihara M (1997) Evaluation of sampling for data mining of association rules. In: Proceedings of the research issues in data engineering, Birmingham, England, 1997","DOI":"10.1109\/RIDE.1997.583696"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-007-0092-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-007-0092-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-007-0092-4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T06:10:16Z","timestamp":1559110216000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-007-0092-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,7,12]]},"references-count":48,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2008,7]]}},"alternative-id":["92"],"URL":"https:\/\/doi.org\/10.1007\/s10115-007-0092-4","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,7,12]]}}}