Abstract
The major part of graph generation is deriving connections (links) between entities (nodes). In this paper, a novel technique RAKE-IDF is introduced for key-phrase extraction across multiple documents. There are two main parts to this work: First is a Contextual Lexicon Generation generation step (in this case, White Collar Crime Lexicon) and second is a text-to-graph generation process. The text-graph generation is an ensemble model of state of the art semantic role labeling models with our key-phrase extraction technique: RAKE-IDF. These two parts are combined by augmenting standard graph with lexicon-generation derived elements to ensure interesting components are represented.
Original language | English |
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Title of host publication | Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 |
Editors | Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4928-4931 |
Number of pages | 4 |
ISBN (Electronic) | 9781728108582 |
DOIs | |
State | Published - Dec 2019 |
Event | 2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: Dec 9 2019 → Dec 12 2019 |
Publication series
Name | Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 |
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Conference
Conference | 2019 IEEE International Conference on Big Data, Big Data 2019 |
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Country/Territory | United States |
City | Los Angeles |
Period | 12/9/19 → 12/12/19 |
Funding
We thank the DARPA Modeling Adversarial Activity (MAA) program for funding this project under contracts HR0011728117, HR001178235, and HR0011729374.