Text Assisted Insight Ranking Using Context-Aware Memory Network [article]

Qi Zeng, Liangchen Luo, Wenhao Huang, Yang Tang
2018 arXiv   pre-print
Extracting valuable facts or informative summaries from multi-dimensional tables, i.e. insight mining, is an important task in data analysis and business intelligence. However, ranking the importance of insights remains a challenging and unexplored task. The main challenge is that explicitly scoring an insight or giving it a rank requires a thorough understanding of the tables and costs a lot of manual efforts, which leads to the lack of available training data for the insight ranking problem.
more » ... n this paper, we propose an insight ranking model that consists of two parts: A neural ranking model explores the data characteristics, such as the header semantics and the data statistical features, and a memory network model introduces table structure and context information into the ranking process. We also build a dataset with text assistance. Experimental results show that our approach largely improves the ranking precision as reported in multi evaluation metrics.
arXiv:1811.05563v1 fatcat:iiplk7ooqfffrcokyu22jpjyzi