{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T09:39:10Z","timestamp":1743068350301,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031206429"},{"type":"electronic","value":"9783031206436"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-20643-6_4","type":"book-chapter","created":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T13:18:09Z","timestamp":1667222289000},"page":"38-52","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Complexity of\u00a0the\u00a0Co-occurrence Problem"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1120-5154","authenticated-orcid":false,"given":"Philip","family":"Bille","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8322-4952","authenticated-orcid":false,"given":"Inge Li","family":"G\u00f8rtz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1525-0104","authenticated-orcid":false,"given":"Tord","family":"Stordalen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,1]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","unstructured":"Amagata, D., Hara, T.: Mining top-$$k$$ co-occurrence patterns across multiple streams (extended abstract). In: Proceeding 34th ICDE, pp. 1747\u20131748 (2018). https:\/\/doi.org\/10.1109\/ICDE.2018.00231","DOI":"10.1109\/ICDE.2018.00231"},{"issue":"2","key":"4_CR2","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/0022-0000(79)90044-8","volume":"18","author":"L Carter","year":"1979","unstructured":"Carter, L., Wegman, M.N.: Universal classes of hash functions. J. Comput. Syst. Sci. 18(2), 143\u2013154 (1979). https:\/\/doi.org\/10.1016\/0022-0000(79)90044-8","journal-title":"J. Comput. Syst. Sci."},{"issue":"8","key":"4_CR3","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.is.2005.04.001","volume":"31","author":"JH Chang","year":"2006","unstructured":"Chang, J.H., Lee, W.S.: Finding recently frequent item sets adaptively over online transactional data streams. Inf. Syst. 31(8), 849\u2013869 (2006). https:\/\/doi.org\/10.1016\/j.is.2005.04.001","journal-title":"Inf. Syst."},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.datak.2013.05.007","volume":"87","author":"M Dallachiesa","year":"2013","unstructured":"Dallachiesa, M., Palpanas, T.: Identifying streaming frequent items in ad hoc time windows. Data Knowl. Eng. 87, 66\u201390 (2013). https:\/\/doi.org\/10.1016\/j.datak.2013.05.007","journal-title":"Data Knowl. Eng."},{"key":"4_CR5","doi-asserted-by":"publisher","unstructured":"Das, G., Fleischer, R., Gasieniec, L., Gunopulos, D., K\u00e4rkk\u00e4inen, J.: Episode matching. In: Proceeding 8th CPM, pp. 12\u201327 (1997). https:\/\/doi.org\/10.1007\/3-540-63220-4_46","DOI":"10.1007\/3-540-63220-4_46"},{"key":"4_CR6","doi-asserted-by":"publisher","unstructured":"Demaine, E.D., L\u00f3pez-Ortiz, A., Munro, J.I.: Frequency estimation of internet packet streams with limited space. In: Proceeding 10th ESA, pp. 348\u2013360 (2002). https:\/\/doi.org\/10.1007\/3-540-45749-6_33","DOI":"10.1007\/3-540-45749-6_33"},{"key":"4_CR7","doi-asserted-by":"publisher","unstructured":"Golab, L., DeHaan, D., Demaine, E.D., L\u00f3pez-Ortiz, A., Munro, J.I.: Identifying frequent items in sliding windows over on-line packet streams. In: Proceeding 3rd ACM IMC, pp. 173\u2013178 (2003). https:\/\/doi.org\/10.1145\/948205.948227","DOI":"10.1145\/948205.948227"},{"key":"4_CR8","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1145\/762471.762473","volume":"28","author":"RM Karp","year":"2003","unstructured":"Karp, R.M., Shenker, S., Papadimitriou, C.H.: A simple algorithm for finding frequent elements in streams and bags. ACM Trans. Database Syst. 28, 51\u201355 (2003). https:\/\/doi.org\/10.1145\/762471.762473","journal-title":"ACM Trans. Database Syst."},{"issue":"2","key":"4_CR9","doi-asserted-by":"publisher","first-page":"1466","DOI":"10.1016\/j.eswa.2007.11.061","volume":"36","author":"H Li","year":"2009","unstructured":"Li, H., Lee, S.: Mining frequent itemsets over data streams using efficient window sliding techniques. Expert Syst. Appl. 36(2), 1466\u20131477 (2009). https:\/\/doi.org\/10.1016\/j.eswa.2007.11.061","journal-title":"Expert Syst. Appl."},{"key":"4_CR10","doi-asserted-by":"publisher","unstructured":"Lim, Y., Choi, J., Kang, U.: Fast, accurate, and space-efficient tracking of time-weighted frequent items from data streams. In: Proceeding 23rd CIKM, pp. 1109\u20131118 (2014). https:\/\/doi.org\/10.1145\/2661829.2662006","DOI":"10.1145\/2661829.2662006"},{"key":"4_CR11","doi-asserted-by":"publisher","unstructured":"Lin, C., Chiu, D., Wu, Y., Chen, A.L.P.: Mining frequent itemsets from data streams with a time-sensitive sliding window. In: Proceeding 5th SDM, pp. 68\u201379 (2005). https:\/\/doi.org\/10.1137\/1.9781611972757.7","DOI":"10.1137\/1.9781611972757.7"},{"key":"4_CR12","doi-asserted-by":"publisher","unstructured":"Mozafari, B., Thakkar, H., Zaniolo, C.: Verifying and mining frequent patterns from large windows over data streams. In: Proceeding 24th ICDE, pp. 179\u2013188 (2008). https:\/\/doi.org\/10.1109\/ICDE.2008.4497426","DOI":"10.1109\/ICDE.2008.4497426"},{"key":"4_CR13","unstructured":"Patrascu, M., Thorup, M.: Randomization does not help searching predecessors. In: Proceedimg 18th SODA, pp. 555\u2013564 (2007). https:\/\/dl.acm.org\/citation.cfm?id=1283383.1283443"},{"key":"4_CR14","doi-asserted-by":"publisher","unstructured":"Sobel, J., Bertram, N., Ding, C., Nargesian, F., Gildea, D.: AWLCO: all-window length co-occurrence. In: Proceeding 32nd CPM, pp. 24:1\u201324:21. LIPIcs (2021). https:\/\/doi.org\/10.4230\/LIPIcs.CPM.2021.24","DOI":"10.4230\/LIPIcs.CPM.2021.24"},{"issue":"2","key":"4_CR15","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/0020-0190(83)90075-3","volume":"17","author":"DE Willard","year":"1983","unstructured":"Willard, D.E.: Log-logarithmic worst-case range queries are possible in space $$\\varTheta (N)$$. Inf. Process. Lett. 17(2), 81\u201384 (1983). https:\/\/doi.org\/10.1016\/0020-0190(83)90075-3","journal-title":"Inf. Process. Lett."},{"key":"4_CR16","doi-asserted-by":"publisher","unstructured":"Yu, Z., Yu, X., Liu, Y., Li, W., Pei, J.: Mining frequent co-occurrence patterns across multiple data streams. In: Proceeding 1th EDBT, pp. 73\u201384 (2015). https:\/\/doi.org\/10.5441\/002\/edbt.2015.08","DOI":"10.5441\/002\/edbt.2015.08"}],"container-title":["Lecture Notes in Computer Science","String Processing and Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20643-6_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T13:19:23Z","timestamp":1667222363000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20643-6_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031206429","9783031206436"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20643-6_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SPIRE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on String Processing and Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Concepci\u00f3n","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chile","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spire2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/spire2022.inf.udec.cl\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"53% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.62","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}