Finding Persistent Items in Data Streams
Summary: Proposes persistent item mining in data streams and introduces PIE, a compact scheme to detect long-term items. PIE encodes IDs with Raptor codes, storing only a few bits per observation window to enable exact recovery with very low FNR; real-trace experiments show up to 19.5x FNR reduction vs prior art. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Haipeng Dai
- 2. Muhammad Shahzad
- 3. Alex X. Liu
- 4. Yuankun Zhong
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,944 | Cold Filter: A Meta-Framework for Faster and More Accurate Stream Processing | 2018 | SIGMOD | 0.00010008078 |
| 3,755 | BurstSketch: Finding Bursts in Data Streams | 2021 | SIGMOD | 6.7822789e-05 |
| 6,791 | On-Off Sketch: A Fast and Accurate Sketch on Persistence | 2021 | VLDB | 4.9204179e-05 |
| 7,731 | Double-Anonymous Sketch: Achieving Top-K-fairness for Finding Global Top-K Frequent Items | 2023 | SIGMOD | 4.6612382e-05 |
| 8,246 | Stingy Sketch: A Sketch Framework for Accurate and Fast Frequency Estimation | 2022 | VLDB | 4.5462498e-05 |
| 10,397 | Pandora: An Efficient and Rapid Solution for Persistence-Based Tasks in High-Speed Data Streams | 2025 | SIGMOD | 4.1905499e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 168 | Approximate Frequency Counts over Data Streams | 2002 | VLDB | 0.0003915627 |
| 831 | Finding Frequent Items in Data Streams | 2008 | VLDB | 0.00016094846 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,443 | Frequent Elements with Witnesses in Data Streams | 2021 | PODS | 4.1905499e-05 |
| 13,810 | Mining Frequent Itemsets with Bit Strings and Trie | 2002 | VLDB | - |
| 5,773 | Mining Frequent Patterns with Differential Privacy | 2013 | VLDB | 5.3300095e-05 |
| 168 | Approximate Frequency Counts over Data Streams | 2002 | VLDB | 0.0003915627 |
| 11,986 | Resource-oriented Approximation for Frequent Itemset Mining from Bursty Data Streams | 2014 | SIGMOD | 4.1905499e-05 |
| 6,339 | A Regression-Based Temporal Pattern Mining Scheme for Data Streams | 2003 | VLDB | 5.0989397e-05 |
| 6,791 | On-Off Sketch: A Fast and Accurate Sketch on Persistence | 2021 | VLDB | 4.9204179e-05 |
| 6,600 | Local Differentially Private Heavy Hitter Detection in Data Streams with Bounded Memory | 2024 | SIGMOD | 4.9925547e-05 |
| 4,451 | False Positive or False Negative: Mining Frequent Itemsets from High Speed Transactional Data Streams | 2004 | VLDB | 6.172063e-05 |
| 831 | Finding Frequent Items in Data Streams | 2008 | VLDB | 0.00016094846 |