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Olga Poppe

8 papers hereh-index 13384 citations29 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author3

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.DB4
  • cs.DC3
  • cs.DS1

identity via Semantic Scholar / OpenAlex

activity
20192024
most citedCloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

21 citations · 48 across the 8 of their papers we have counts for

collaborators
Showing cs.DBShow all

4 papers · 1 filter

cs.DB2021

To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams

Olga Poppe, Chuan Lei, Lei Ma +2

Complex event processing (CEP) systems continuously evaluate large workloads of pattern queries under tight time constraints. Event trend aggregation queries with Kleene patterns a…

cs.DB2020

Sharon: Shared Online Event Sequence Aggregation

Olga Poppe, Allison Rozet, Chuan Lei +2

Streaming systems evaluate massive workloads of event sequence aggregation queries. State-of-the-art approaches suffer from long delays caused by not sharing intermediate results o…

cs.DB2020

Event Trend Aggregation Under Rich Event Matching Semantics

Olga Poppe, Chuan Lei, Elke A. Rundensteiner +1

Streaming applications from health care analytics to algorithmic trading deploy Kleene queries to detect and aggregate event trends. Rich event matching semantics determine how to…

cs.DB2019★ 21 cited

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

Ashvin Agrawal, Rony Chatterjee, Carlo Curino +19

Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios inc…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.