Synthesis and machine learning for heterogeneous extraction
Arun Shankar Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram K. Rajamani · 2019
We present a way to combine techniques from the program synthesis and machine learning communities to extract structured information from heterogeneous data. Such problems arise in several situations such as extracting attributes from web pages, machine-generated emails, or from data obtained from multiple sources. Our goal is to extract a set of structured attributes from such data.