ItemSuggest: A Data Management Platform for Machine Learned Ranking Services
Summary: ItemSuggest is a data-management–centric platform for building contextual ML ranking services that streamlines training-data collection, quality validation/monitoring, feature lifecycle, model training/eval and A/B testing to maximize experiment velocity. It reports large-scale production lessons and highlights research avenues in transformation engines for feature engineering and compact training-set representations. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sandeep Tata (Google)
- 2. Vlad Panait (Google)
- 3. Suming J. Chen (Google)
- 4. Mike Colagrosso (Google)
BibTeX Citation
@inproceedings{tata_cidr19,
address = {Amsterdam, Netherlands},
series = {{CIDR} '19},
title = {{ItemSuggest: A Data Management Platform for Machine Learned Ranking Services}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Tata, Sandeep and Panait, Vlad and Chen, Suming J. and Colagrosso, Mike},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,614 | Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation | 2021 | CIDR | 5.2444447e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 963 | The Data Civilizer System | 2017 | CIDR | 0.00012935145 |
| 1,147 | Data Management Challenges in Production Machine Learning | 2017 | SIGMOD | 0.00011974846 |
| 1,250 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD | 0.00011485301 |
| 6,945 | Building Machine Learning Systems that Understand | 2016 | SIGMOD | 5.7309872e-05 |
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