Entity Set Co-Expansion in StackOverflow
December 05, 2022 ยท Declared Dead ยท ๐ 2022 IEEE International Conference on Big Data (Big Data)
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Authors
Yu Zhang, Yunyi Zhang, Yucheng Jiang, Martin Michalski, Yu Deng, Lucian Popa, ChengXiang Zhai, Jiawei Han
arXiv ID
2212.02271
Category
cs.CL: Computation & Language
Cross-listed
cs.SE
Citations
4
Venue
2022 IEEE International Conference on Big Data (Big Data)
Last Checked
5 months ago
Abstract
Given a few seed entities of a certain type (e.g., Software or Programming Language), entity set expansion aims to discover an extensive set of entities that share the same type as the seeds. Entity set expansion in software-related domains such as StackOverflow can benefit many downstream tasks (e.g., software knowledge graph construction) and facilitate better IT operations and service management. Meanwhile, existing approaches are less concerned with two problems: (1) How to deal with multiple types of seed entities simultaneously? (2) How to leverage the power of pre-trained language models (PLMs)? Being aware of these two problems, in this paper, we study the entity set co-expansion task in StackOverflow, which extracts Library, OS, Application, and Language entities from StackOverflow question-answer threads. During the co-expansion process, we use PLMs to derive embeddings of candidate entities for calculating similarities between entities. Experimental results show that our proposed SECoExpan framework outperforms previous approaches significantly.
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