MGNETS: Multi-Graph Neural Networks for Table Search

Conference on Information and Knowledge Management(2021)

Cited 3|Views44
No score
Abstract
BSTRACTTable search aims to retrieve a list of tables given a user's query. Previous methods only consider the textual information of tables and the structural information is rarely used. In this paper, we propose to model the complex relations in the table corpus as one or more graphs and then utilize graph neural networks to learn representations of queries and tables. We show that the text-based table retrieval methods can be further improved by graph-based predictions which fuse multiple field-level information.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined