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ORCIDLan Li 0002
Person information
- affiliation: University of Illinois at Urbana-Champaign, IL, USA
Other persons with the same name
- Lan Li — disambiguation page
- Lan Li 0001 — Nanjing University, Nanjing, China
- Lan Li 0003 — University of Texas at Austin, Austin, TX, USA
- Lan Li 0004 — Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China
- Lan Li 0005
![[0000-0002-3175-4169]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-3175-4169")
— Dalian Maritime University, Dalian, China
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2020 – today
- 2024
[j3]Lan Li, Liri Fang, Yiren Liu, Bertram Ludäscher, Vetle I. Torvik:
T-KAER: Transparency-enhanced Knowledge-Augmented Entity Resolution Framework. Int. J. Digit. Curation 18(1): 14 (2024)- [i4]Yilin Xia, Shawn Bowers, Lan Li, Bertram Ludäscher:
Reconciling Conflicting Data Curation Actions: Transparency Through Argumentation. CoRR abs/2403.08257 (2024) - [i3]Lan Li, Liri Fang, Yiren Liu, Vetle I. Torvik, Bertram Ludäscher:
T-KAER: Transparency-enhanced Knowledge-Augmented Entity Resolution Framework. CoRR abs/2410.00218 (2024) - 2023
- [i2]Liri Fang, Lan Li, Yiren Liu, Vetle I. Torvik, Bertram Ludäscher:
KAER: A Knowledge Augmented Pre-Trained Language Model for Entity Resolution. CoRR abs/2301.04770 (2023) - 2022
- [j2]Lan Li, Bertram Ludäscher:
On the Reusability of Data Cleaning Workflows. Int. J. Digit. Curation 17(1): 6 (2022) - 2021
- [j1]Lan Li, Nikolaus Parulian, Bertram Ludäscher:
Automatic Module Detection in Data Cleaning Workflows: Enabling Transparency and Recipe Reuse. Int. J. Digit. Curation 16(1): 11 (2021) - [i1]Nikolaus Nova Parulian, Lan Li, Bertram Ludäscher:
or2yw: Modeling and Visualizing OpenRefineHistories as YesWorkflow Diagrams. CoRR abs/2112.08259 (2021) - 2020
- [c2]Santiago Núñez Corrales, Lan Li, Bertram Ludäscher:
A First-Principles Algebraic Approach to Data Transformations in Data Cleaning: Understanding Provenance from the Ground Up. TaPP 2020
2010 – 2019
- 2019
- [c1]Timothy M. McPhillips, Lan Li, Nikolaus Nova Parulian, Bertram Ludäscher:
Modeling Provenance and Understanding Reproducibility for OpenRefine Data Cleaning Workflows. TaPP 2019
Coauthor Index
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