6 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
The Battleship Approach to the Low Resource Entity Matching Problem
Bar Genossar, Avigdor Gal, Roee Shraga
Entity matching, a core data integration problem, is the task of deciding whether two data tuples refer to the same real-world entity. Recent advances in deep learning methods, usi…
SANTOS: Relationship-based Semantic Table Union Search
Aamod Khatiwada, Grace Fan, Roee Shraga +4
Existing techniques for unionable table search define unionability using metadata (tables must have the same or similar schemas) or column-based metrics (for example, the values in…
HumanAL: Calibrating Human Matching Beyond a Single Task
Roee Shraga
This work offers a novel view on the use of human input as labels, acknowledging that humans may err. We build a behavioral profile for human annotators which is used as a feature…
Human's Role in-the-Loop
Avigdor Gal, Roee Shraga
Data integration has been recently challenged by the need to handle large volumes of data, arriving at high velocity from a variety of sources, which demonstrate varying levels of…
PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema Matching
Roee Shraga, Avigdor Gal
Schema matching is a core task of any data integration process. Being investigated in the fields of databases, AI, Semantic Web and data mining for many years, the main challenge r…
Learning to Characterize Matching Experts
Roee Shraga, Ofra Amir, Avigdor Gal
Matching is a task at the heart of any data integration process, aimed at identifying correspondences among data elements. Matching problems were traditionally solved in a semi-aut…