Entity Matching Meets Data Science: A Progress Report from the Magellan Project. - Yash Govind; Pradap Konda; Paul Suganthan G. C.; Philip Martinkus; Palaniappan Nagarajan; Han Li; Aravind Soundararajan; Sidharth Mudgal; Jeffrey R. Ballard; Haojun Zhang; Adel Ardalan; Sanjib Das; et al. (SIGMOD Conference, 2019)

Magellan: toward building ecosystems of entity matching solutions. - AnHai Doan; Pradap Konda; Paul Suganthan G. C.; Yash Govind; Derek Paulsen; Kaushik Chandrasekhar; Philip Martinkus; Matthew Christie (Commun. ACM, 2020)

Deep Learning for Blocking in Entity Matching: A Design Space Exploration. - Saravanan Thirumuruganathan; Han Li; Nan Tang 001; Mourad Ouzzani; Yash Govind; Derek Paulsen; Glenn Fung; AnHai Doan (Proc. VLDB Endow., 2021)

Toward Data Cleaning with a Target Accuracy: A Case Study for Value Normalization. - Adel Ardalan; Derek Paulsen; Amanpreet Singh Saini; Walter Cai; AnHai Doan (IEEE Big Data, 2022)

Sparkly: A Simple yet Surprisingly Strong TF/IDF Blocker for Entity Matching. - Derek Paulsen; Yash Govind; AnHai Doan (Proc. VLDB Endow., 2023)