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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Text Assisted Insight Ranking Using Context-Aware Memory Network

February 1, 2023

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Authors

Qi Zeng

Stony Brook University


Liangchen Luo

Peking University


Wenhao Huang

Shanghai Discovering Investment


Yang Tang

Peking University


DOI:

10.1609/aaai.v33i01.3301427


Abstract:

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. In 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.

Topics: AAAI

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HOW TO CITE:

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang Text Assisted Insight Ranking Using Context-Aware Memory Network Proceedings of the AAAI Conference on Artificial Intelligence (2019) 427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang Text Assisted Insight Ranking Using Context-Aware Memory Network AAAI 2019, 427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang (2019). Text Assisted Insight Ranking Using Context-Aware Memory Network. Proceedings of the AAAI Conference on Artificial Intelligence, 427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. Text Assisted Insight Ranking Using Context-Aware Memory Network. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. 2019. Text Assisted Insight Ranking Using Context-Aware Memory Network. "Proceedings of the AAAI Conference on Artificial Intelligence". 427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. (2019) "Text Assisted Insight Ranking Using Context-Aware Memory Network", Proceedings of the AAAI Conference on Artificial Intelligence, p.427-434

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang, "Text Assisted Insight Ranking Using Context-Aware Memory Network", AAAI, p.427-434, 2019.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. "Text Assisted Insight Ranking Using Context-Aware Memory Network". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. "Text Assisted Insight Ranking Using Context-Aware Memory Network". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 427-434.

Qi Zeng||Liangchen Luo||Wenhao Huang||Yang Tang. Text Assisted Insight Ranking Using Context-Aware Memory Network. AAAI[Internet]. 2019[cited 2023]; 427-434.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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