{"paper":{"title":"The Online Event-Detection Problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Cynthia A. Phillips, Jonathan W. Berry, Martin Farach-Colton, Michael A. Bender, Prashant Pandey, Rob Johnson, Shikha Singh, Thomas M. Kroeger","submitted_at":"2018-12-24T04:16:53Z","abstract_excerpt":"Given a stream $S = (s_1, s_2, ..., s_N)$, a $\\phi$-heavy hitter is an item $s_i$ that occurs at least $\\phi N$ times in $S$. The problem of finding heavy-hitters has been extensively studied in the database literature. In this paper, we study a related problem. We say that there is a $\\phi$-event at time $t$ if $s_t$ occurs exactly $\\phi N$ times in $(s_1, s_2, ..., s_t)$. Thus, for each $\\phi$-heavy hitter there is a single $\\phi$-event which occurs when its count reaches the reporting threshold $\\phi N$. We define the online event-detection problem (OEDP) as: given $\\phi$ and a stream $S$, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.09824","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}