{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T19:05:32Z","timestamp":1772823932037,"version":"3.50.1"},"reference-count":52,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T00:00:00Z","timestamp":1607299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Italian Ministry of University and Research","award":["20174LF3T8"],"award-info":[{"award-number":["20174LF3T8"]}]},{"name":"Netherlands Organization for Scientific Research","award":["NETWORKS-024.002.003"],"award-info":[{"award-number":["NETWORKS-024.002.003"]}]},{"DOI":"10.13039\/501100010890","name":"Chinese Government Scholarship","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010890","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007514","name":"University of Pisa","doi-asserted-by":"crossref","award":["PRA_2020-2021_2"],"award-info":[{"award-number":["PRA_2020-2021_2"]}],"id":[{"id":"10.13039\/501100007514","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2021,2,28]]},"abstract":"<jats:p>String data are often disseminated to support applications such as location-based service provision or DNA sequence analysis. This dissemination, however, may expose sensitive patterns that model confidential knowledge (e.g., trips to mental health clinics from a string representing a user\u2019s location history). In this article, we consider the problem of sanitizing a string by concealing the occurrences of sensitive patterns, while maintaining data utility, in two settings that are relevant to many common string processing tasks.<\/jats:p>\n          <jats:p>In the first setting, we aim to generate the minimal-length string that preserves the order of appearance and frequency of all non-sensitive patterns. Such a string allows accurately performing tasks based on the sequential nature and pattern frequencies of the string. To construct such a string, we propose a time-optimal algorithm, TFS-ALGO. We also propose another time-optimal algorithm, PFS-ALGO, which preserves a partial order of appearance of non-sensitive patterns but produces a much shorter string that can be analyzed more efficiently. The strings produced by either of these algorithms are constructed by concatenating non-sensitive parts of the input string. However, it is possible to detect the sensitive patterns by \u201creversing\u201d the concatenation operations. In response, we propose a heuristic, MCSR-ALGO, which replaces letters in the strings output by the algorithms with carefully selected letters, so that sensitive patterns are not reinstated, implausible patterns are not introduced, and occurrences of spurious patterns are prevented. In the second setting, we aim to generate a string that is at minimal edit distance from the original string, in addition to preserving the order of appearance and frequency of all non-sensitive patterns. To construct such a string, we propose an algorithm, ETFS-ALGO, based on solving specific instances of approximate regular expression matching.<\/jats:p>\n          <jats:p>We implemented our sanitization approach that applies TFS-ALGO, PFS-ALGO, and then MCSR-ALGO, and experimentally show that it is effective and efficient. We also show that TFS-ALGO is nearly as effective at minimizing the edit distance as ETFS-ALGO, while being substantially more efficient than ETFS-ALGO.<\/jats:p>","DOI":"10.1145\/3418683","type":"journal-article","created":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T19:04:16Z","timestamp":1607367856000},"page":"1-34","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Combinatorial Algorithms for String Sanitization"],"prefix":"10.1145","volume":"15","author":[{"given":"Giulia","family":"Bernardini","sequence":"first","affiliation":[{"name":"University of Milano - Bicocca and CWI, Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huiping","family":"Chen","sequence":"additional","affiliation":[{"name":"King\u2019s College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessio","family":"Conte","sequence":"additional","affiliation":[{"name":"University of Pisa, Largo Pontecorvo, Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Grossi","sequence":"additional","affiliation":[{"name":"University of Pisa and ERABLE Team, Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Grigorios","family":"Loukides","sequence":"additional","affiliation":[{"name":"King\u2019s College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadia","family":"Pisanti","sequence":"additional","affiliation":[{"name":"University of Pisa and ERABLE Team, Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Solon P.","family":"Pissis","sequence":"additional","affiliation":[{"name":"CWI, Vrije Universiteit Amsterdam, and ERABLE Team, Amsterdam, NETHERLANDS"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giovanna","family":"Rosone","sequence":"additional","affiliation":[{"name":"University of Pisa, Largo Pontecorvo, Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michelle","family":"Sweering","sequence":"additional","affiliation":[{"name":"CWI, Amsterdam, NETHERLANDS"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,12,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.213"},{"key":"e_1_2_1_2_1","volume-title":"Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques","author":"Abul Osman","unstructured":"Osman Abul . 2010. Knowledge hiding in emerging application domains . In Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques . CRC Press . Osman Abul. 2010. Knowledge hiding in emerging application domains. In Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques. CRC Press."},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 2007 SIAM International Conference on Data Mining. 419--424","author":"Aggarwal C. C.","unstructured":"C. C. Aggarwal and P. S. Yu . 2007. On anonymization of string data . In Proceedings of the 2007 SIAM International Conference on Data Mining. 419--424 . C. C. Aggarwal and P. S. Yu. 2007. On anonymization of string data. In Proceedings of the 2007 SIAM International Conference on Data Mining. 419--424."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-008-0088-z"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"C. C. Aggarwal and P. S. Yu. 2008. A general survey of privacy-preserving data mining models and algorithms. In Privacy-Preserving Data Mining: Models and Algorithms. Springer.  C. C. Aggarwal and P. S. Yu. 2008. A general survey of privacy-preserving data mining models and algorithms. In Privacy-Preserving Data Mining: Models and Algorithms. Springer.","DOI":"10.1007\/978-0-387-70992-5"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","unstructured":"C. C. Aggarwal and P. S. Yu. 2008. Privacy-Preserving Data Mining: Models and Algorithms. Springer.  C. C. Aggarwal and P. S. Yu. 2008. Privacy-Preserving Data Mining: Models and Algorithms. Springer.","DOI":"10.1007\/978-0-387-70992-5"},{"key":"e_1_2_1_7_1","volume-title":"On avoided words, absent words, and their application to biological sequence analysis. Algorithms for Molecular Biology 12, 5","author":"Almirantis Yannis","year":"2017","unstructured":"Yannis Almirantis , Panagiotis Charalampopoulos , Jia Gao , Costas S. Iliopoulos , Manal Mohamed , Solon P. Pissis , and Dimitris Polychronopoulos . 2017. On avoided words, absent words, and their application to biological sequence analysis. Algorithms for Molecular Biology 12, 5 ( 2017 ). Yannis Almirantis, Panagiotis Charalampopoulos, Jia Gao, Costas S. Iliopoulos, Manal Mohamed, Solon P. Pissis, and Dimitris Polychronopoulos. 2017. On avoided words, absent words, and their application to biological sequence analysis. Algorithms for Molecular Biology 12, 5 (2017)."},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the 47th Annual ACM Symposium on Theory of Computing. 51--58","author":"Backurs A.","unstructured":"A. Backurs and P. Indyk . 2015. Edit distance cannot be computed in strongly subquadratic time (Unless SETH is false) . In Proceedings of the 47th Annual ACM Symposium on Theory of Computing. 51--58 . A. Backurs and P. Indyk. 2015. Edit distance cannot be computed in strongly subquadratic time (Unless SETH is false). In Proceedings of the 47th Annual ACM Symposium on Theory of Computing. 51--58."},{"key":"e_1_2_1_9_1","first-page":"1","article-title":"String sanitization under edit distance","volume":"7","author":"Bernardini G.","year":"2020","unstructured":"G. Bernardini , H. Chen , G. Loukides , N. Pisanti , S. P. Pissis , L. Stougie , and M. Sweering . 2020 . String sanitization under edit distance . In Proceedings of the Annual Symposium on Combinatorial Pattern Matching. 7 : 1 -- 7 :14. G. Bernardini, H. Chen, G. Loukides, N. Pisanti, S. P. Pissis, L. Stougie, and M. Sweering. 2020. String sanitization under edit distance. In Proceedings of the Annual Symposium on Combinatorial Pattern Matching. 7:1--7:14.","journal-title":"Proceedings of the Annual Symposium on Combinatorial Pattern Matching."},{"key":"e_1_2_1_10_1","volume-title":"Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 627--644","author":"Bernardini Giulia","year":"2019","unstructured":"Giulia Bernardini , Huiping Chen , Alessio Conte , Roberto Grossi , Grigorios Loukides , Nadia Pisanti , Solon P. Pissis , and Giovanna Rosone . 2019 . String sanitization: A combinatorial approach . In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 627--644 . Giulia Bernardini, Huiping Chen, Alessio Conte, Roberto Grossi, Grigorios Loukides, Nadia Pisanti, Solon P. Pissis, and Giovanna Rosone. 2019. String sanitization: A combinatorial approach. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 627--644."},{"key":"e_1_2_1_11_1","volume-title":"Pissis","author":"Bernardini Giulia","year":"2020","unstructured":"Giulia Bernardini , Huiping Chen , Gabriele Fici , Grigorios Loukides , and Solon P . Pissis . 2020 . Reverse-safe data structures for text indexing. In Proceedings of the Symposium on Algorithm Engineering and Experiments. SIAM , 199--213. Giulia Bernardini, Huiping Chen, Gabriele Fici, Grigorios Loukides, and Solon P. Pissis. 2020. Reverse-safe data structures for text indexing. In Proceedings of the Symposium on Algorithm Engineering and Experiments. SIAM, 199--213."},{"key":"e_1_2_1_12_1","doi-asserted-by":"crossref","unstructured":"F. Bonchi and E. Ferrari. 2010. Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques. CRC Press.  F. Bonchi and E. Ferrari. 2010. Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques. CRC Press.","DOI":"10.1201\/b10373"},{"key":"e_1_2_1_13_1","volume-title":"Proceedings of the 9th ACM International Conference on Web Search and Data Mining. 337--346","author":"Bonomi L.","unstructured":"L. Bonomi , L. Fan , and H. Jin . 2016. An information-theoretic approach to individual sequential data sanitization . In Proceedings of the 9th ACM International Conference on Web Search and Data Mining. 337--346 . L. Bonomi, L. Fan, and H. Jin. 2016. An information-theoretic approach to individual sequential data sanitization. In Proceedings of the 9th ACM International Conference on Web Search and Data Mining. 337--346."},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. 269--278","author":"Bonomi L.","unstructured":"L. Bonomi and L. Xiong . 2013. A two-phase algorithm for mining sequential patterns with differential privacy . In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. 269--278 . L. Bonomi and L. Xiong. 2013. A two-phase algorithm for mining sequential patterns with differential privacy. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. 269--278."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1080\/07391102.1986.10507643"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcss.2016.06.008"},{"key":"e_1_2_1_17_1","volume-title":"Proceedings of the 2012 ACM Conference on Computer and Communications Security. 638--649","author":"Chen R.","unstructured":"R. Chen , G. Acs , and C. Castelluccia . 2012. Differentially private sequential data publication via variable-length N-grams . In Proceedings of the 2012 ACM Conference on Computer and Communications Security. 638--649 . R. Chen, G. Acs, and C. Castelluccia. 2012. Differentially private sequential data publication via variable-length N-grams. In Proceedings of the 2012 ACM Conference on Computer and Communications Security. 638--649."},{"key":"e_1_2_1_18_1","volume-title":"Proceedings of the IEEE 24th International Conference on Data Engineering. 1379--1381","author":"Cormode G.","unstructured":"G. Cormode , F. Korn , and S. Tirthapura . 2008. Exponentially decayed aggregates on data streams . In Proceedings of the IEEE 24th International Conference on Data Engineering. 1379--1381 . G. Cormode, F. Korn, and S. Tirthapura. 2008. Exponentially decayed aggregates on data streams. In Proceedings of the IEEE 24th International Conference on Data Engineering. 1379--1381."},{"key":"e_1_2_1_19_1","doi-asserted-by":"crossref","unstructured":"M. Crochemore C. Hancart and T. Lecroq. 2007. Algorithms on Strings. Cambridge University Press.  M. Crochemore C. Hancart and T. Lecroq. 2007. Algorithms on Strings. Cambridge University Press.","DOI":"10.1017\/CBO9780511546853"},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. 4358--4361","author":"Droppo J.","unstructured":"J. Droppo and A. Acero . 2010. Context dependent phonetic string edit distance for automatic speech recognition . In Proceedings of the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. 4358--4361 . J. Droppo and A. Acero. 2010. Context dependent phonetic string edit distance for automatic speech recognition. In Proceedings of the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. 4358--4361."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the Theory of Cryptography Conference. 265--284","author":"Dwork C.","unstructured":"C. Dwork , F. McSherry , K. Nissim , and A. Smith . 2006. Calibrating noise to sensitivity in private data analysis . In Proceedings of the Theory of Cryptography Conference. 265--284 . C. Dwork, F. McSherry, K. Nissim, and A. Smith. 2006. Calibrating noise to sensitivity in private data analysis. In Proceedings of the Theory of Cryptography Conference. 265--284."},{"key":"e_1_2_1_22_1","volume-title":"Encyclopedia of Cryptography and Security","author":"Foresti Sara","unstructured":"Sara Foresti . 2011. Microdata protection . In Encyclopedia of Cryptography and Security , 2 nd Ed, Henk C.A. van Tilborg, and Sushil Jajodia (Eds.). Springer , 781--783. Sara Foresti. 2011. Microdata protection. In Encyclopedia of Cryptography and Security, 2nd Ed, Henk C.A. van Tilborg, and Sushil Jajodia (Eds.). Springer, 781--783.","edition":"2"},{"key":"e_1_2_1_23_1","volume-title":"Yu","author":"Fung Benjamin C. M.","year":"2010","unstructured":"Benjamin C. M. Fung , Ke Wang , Rui Chen , and Philip S . Yu . 2010 . Privacy-preserving data publishing: A survey of recent developments. ACM Computing Surveys 42, 4, (June 2010), 53. Benjamin C. M. Fung, Ke Wang, Rui Chen, and Philip S. Yu. 2010. Privacy-preserving data publishing: A survey of recent developments. ACM Computing Surveys 42, 4, (June 2010), 53."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-0000(80)90004-5"},{"key":"e_1_2_1_25_1","volume-title":"Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1316--1324","author":"Gkoulalas-Divanis A.","unstructured":"A. Gkoulalas-Divanis and G. Loukides . 2011. Revisiting sequential pattern hiding to enhance utility . In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1316--1324 . A. Gkoulalas-Divanis and G. Loukides. 2011. Revisiting sequential pattern hiding to enhance utility. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1316--1324."},{"key":"e_1_2_1_26_1","volume-title":"Circular sequence comparison: Algorithms and applications. Algorithms for Molecular Biology 11, 12","author":"Grossi Roberto","year":"2016","unstructured":"Roberto Grossi , Costas S. Iliopoulos , Robert Mercas , Nadia Pisanti , Solon P. Pissis , Ahmad Retha , and Fatima Vayani . 2016. Circular sequence comparison: Algorithms and applications. Algorithms for Molecular Biology 11, 12 ( 2016 ). Roberto Grossi, Costas S. Iliopoulos, Robert Mercas, Nadia Pisanti, Solon P. Pissis, Ahmad Retha, and Fatima Vayani. 2016. Circular sequence comparison: Algorithms and applications. Algorithms for Molecular Biology 11, 12 (2016)."},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the 2013 IEEE 13th International Conference on Data Mining. 241--250","author":"Gwadera R.","unstructured":"R. Gwadera , A. Gkoulalas-Divanis , and G. Loukides . 2013. Permutation-based sequential pattern hiding . In Proceedings of the 2013 IEEE 13th International Conference on Data Mining. 241--250 . R. Gwadera, A. Gkoulalas-Divanis, and G. Loukides. 2013. Permutation-based sequential pattern hiding. In Proceedings of the 2013 IEEE 13th International Conference on Data Mining. 241--250."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-007-0061-2"},{"key":"e_1_2_1_29_1","volume-title":"The Multiple-Choice Knapsack Problem","author":"Kellerer Hans","unstructured":"Hans Kellerer , Ulrich Pferschy , and David Pisinger . 2004. The Multiple-Choice Knapsack Problem . Springer , Berlin , 317--347. Hans Kellerer, Ulrich Pferschy, and David Pisinger. 2004. The Multiple-Choice Knapsack Problem. Springer, Berlin, 317--347."},{"key":"e_1_2_1_30_1","volume-title":"Proceedings of the IEEE International Conference on Data Engineering. 66--77","author":"Liu A.","unstructured":"A. Liu , K. Zhengy , L. Liz , G. Liu , L. Zhao , and X. Zhou . 2015. Efficient secure similarity computation on encrypted trajectory data . In Proceedings of the IEEE International Conference on Data Engineering. 66--77 . A. Liu, K. Zhengy, L. Liz, G. Liu, L. Zhao, and X. Zhou. 2015. Efficient secure similarity computation on encrypted trajectory data. In Proceedings of the IEEE International Conference on Data Engineering. 66--77."},{"key":"e_1_2_1_31_1","volume-title":"Proceedings of the 2015 SIAM International Conference on Data Mining. 775--783","author":"Loukides G.","unstructured":"G. Loukides and R. Gwadera . 2015. Optimal event sequence sanitization . In Proceedings of the 2015 SIAM International Conference on Data Mining. 775--783 . G. Loukides and R. Gwadera. 2015. Optimal event sequence sanitization. In Proceedings of the 2015 SIAM International Conference on Data Mining. 775--783."},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0911686107"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2309131"},{"key":"e_1_2_1_34_1","unstructured":"B. Malin and L. Sweeney. 2000. Determining the identifiability of DNA database entries. In AMIA. 537--541.  B. Malin and L. Sweeney. 2000. Determining the identifiability of DNA database entries. In AMIA. 537--541."},{"key":"e_1_2_1_35_1","volume-title":"Manning and Hinrich Sch\u00fctze","author":"Christopher","year":"1999","unstructured":"Christopher D. Manning and Hinrich Sch\u00fctze . 1999 . Foundations of Statistical Natural Language Processing. MIT Press , Cambridge, MA. Christopher D. Manning and Hinrich Sch\u00fctze. 1999. Foundations of Statistical Natural Language Processing. MIT Press, Cambridge, MA."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10506-014-9154-6"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02458834"},{"key":"e_1_2_1_38_1","volume-title":"Proceedings of the 2008 IEEE Symposium on Security and Privacy. 111--125","author":"Narayanan A.","unstructured":"A. Narayanan and V. Shmatikov . 2008. Robust de-anonymization of large sparse datasets . In Proceedings of the 2008 IEEE Symposium on Security and Privacy. 111--125 . A. Narayanan and V. Shmatikov. 2008. Robust de-anonymization of large sparse datasets. In Proceedings of the 2008 IEEE Symposium on Security and Privacy. 111--125."},{"key":"e_1_2_1_39_1","doi-asserted-by":"crossref","unstructured":"J. Natwichai X. Li and M. Orlowska. 2005. Hiding classification rules for data sharing with privacy preservation. In Data Warehousing and Knowledge Discovery. Springer Berlin 468--477.  J. Natwichai X. Li and M. Orlowska. 2005. Hiding classification rules for data sharing with privacy preservation. In Data Warehousing and Knowledge Discovery. Springer Berlin 468--477.","DOI":"10.1007\/11546849_46"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(95)00015-I"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-15-235"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720006002028"},{"key":"e_1_2_1_43_1","volume-title":"Proceedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. 188","author":"Samarati P.","unstructured":"P. Samarati and L. Sweeney . 1998. Generalizing data to provide anonymity when disclosing information (abstract) . In Proceedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. 188 . P. Samarati and L. Sweeney. 1998. Generalizing data to provide anonymity when disclosing information (abstract). In Proceedings of the 17th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. 188."},{"key":"e_1_2_1_44_1","volume-title":"Proceedings of the 2016 SIAM International Conference on Data Mining. 558--566","author":"Shang J.","unstructured":"J. Shang , J. Peng , and J. Han . [2016]. MACFP: Maximal approximate consecutive frequent pattern mining under edit distance . In Proceedings of the 2016 SIAM International Conference on Data Mining. 558--566 . J. Shang, J. Peng, and J. Han. [2016]. MACFP: Maximal approximate consecutive frequent pattern mining under edit distance. In Proceedings of the 2016 SIAM International Conference on Data Mining. 558--566."},{"key":"e_1_2_1_45_1","doi-asserted-by":"crossref","unstructured":"P. Sinha and A. A. Zoltners. 1979. The multiple-choice knapsack problem.Operations Research 27 3 (1979) 431--627.  P. Sinha and A. A. Zoltners. 1979. The multiple-choice knapsack problem.Operations Research 27 3 (1979) 431--627.","DOI":"10.1287\/opre.27.3.503"},{"key":"e_1_2_1_46_1","volume-title":"Proceedings of the 5th IEEE International Conference on Data Mining. 426--433","author":"Sun X.","unstructured":"X. Sun and P.S. Yu . 2005. A border-based approach for hiding sensitive frequent itemsets . In Proceedings of the 5th IEEE International Conference on Data Mining. 426--433 . X. Sun and P.S. Yu. 2005. A border-based approach for hiding sensitive frequent itemsets. In Proceedings of the 5th IEEE International Conference on Data Mining. 426--433."},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2675420"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/2665943.2665946"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2004.1269668"},{"key":"e_1_2_1_50_1","volume-title":"Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 589--600","author":"Wang D.","unstructured":"D. Wang , Y. He , E. Rundensteiner , and J. F. Naughton . 2013. Utility-maximizing event stream suppression . In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 589--600 . D. Wang, Y. He, E. Rundensteiner, and J. F. Naughton. 2013. Utility-maximizing event stream suppression. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 589--600."},{"key":"e_1_2_1_51_1","volume-title":"Proceedings of the IEEE International Conference on Data Engineering. 998--1009","author":"Wen Z.","unstructured":"Z. Wen , D. Deng , R. Zhang , and R. Kotagiri . 2019. 2ED: An efficient entity extraction algorithm using two-level edit-distance . In Proceedings of the IEEE International Conference on Data Engineering. 998--1009 . Z. Wen, D. Deng, R. Zhang, and R. Kotagiri. 2019. 2ED: An efficient entity extraction algorithm using two-level edit-distance. In Proceedings of the IEEE International Conference on Data Engineering. 998--1009."},{"key":"e_1_2_1_52_1","volume-title":"Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 767--775","author":"Xu Y.","unstructured":"Y. Xu , K. Wang , A. W. Fu , and P. S. Yu . 2008. Anonymizing transaction databases for publication . In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 767--775 . Y. Xu, K. Wang, A. W. Fu, and P. S. Yu. 2008. Anonymizing transaction databases for publication. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 767--775."}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3418683","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3418683","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:28Z","timestamp":1750197748000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3418683"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,7]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,2,28]]}},"alternative-id":["10.1145\/3418683"],"URL":"https:\/\/doi.org\/10.1145\/3418683","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"value":"1556-4681","type":"print"},{"value":"1556-472X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,7]]},"assertion":[{"value":"2019-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-08-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-12-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}