Taxonomy Maintenance in the Wild over Evolving Scholarly Data: Reliability, Efficiency, and Cost-Effectiveness

Summary: GIST continuously updates scholarly taxonomies by grounding hierarchy induction in paper Related Work sections, then integrating evidence with box embeddings that encode is-a relations. Novelty-aware coreset updates and budget-aware retrieval improve accuracy while sharply reducing runtime and LLM cost. (summarized by gpt-6-luna on Oct 22 2026)

Paper ID: hbfd0c86f5b4ea31f
Venue: SIGMOD
Year: 2027
Pagerank: 4.9605343e-05
Overall Rank: 10,412 | 30.21%
DOI: 10.1145/3837127
PDF: Download (CC BY 4.0)

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Daomin Ji (RMIT University; University of Queensland)
2. Hui Luo (University of Wollongong)
3. Zhifeng Bao (University of Queensland)
4. Junhao Gan (University of Melbourne)
5. Zi Huang (University of Queensland)

BibTeX Citation

@inproceedings{ji_sigmod27,
        title = {{Taxonomy Maintenance in the Wild over Evolving Scholarly Data: Reliability, Efficiency, and Cost-Effectiveness}},
        author = {Ji, Daomin and Luo, Hui and Bao, Zhifeng and Gan, Junhao and Huang, Zi},
        series = {{SIGMOD} '27},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3837127},
        url = {https://dl.acm.org/doi/10.1145/3837127},
        year = {2027}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
132	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.00030213215
430	ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores	2016	VLDB	0.00018415668
517	Magellan: Toward Building Entity Matching Management Systems	2016	VLDB	0.00016946929
569	Incremental Knowledge Base Construction Using DeepDive	2015	VLDB	0.00016212139
2,942	Fonduer: Knowledge Base Construction from Richly Formatted Data	2018	SIGMOD	7.8171618e-05
3,166	Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration	2023	SIGMOD	7.5597853e-05
3,757	GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data	2023	SIGMOD	7.0254733e-05
4,384	Knowledge Graphs 2021: A Data Odyssey	2021	VLDB	6.6139064e-05
5,256	Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior	2012	VLDB	6.1962326e-05
6,654	Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning	2023	VLDB	5.7038474e-05
7,028	Are Large Language Models a Good Replacement of Taxonomies?	2024	VLDB	5.6012052e-05
7,428	Optimizing Index for Taxonomy Keyword Search	2012	SIGMOD	5.5140463e-05
7,601	Robust Entity Resolution using Random Graphs	2018	SIGMOD	5.4714372e-05
8,096	Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection	2025	SIGMOD	5.3739121e-05
8,397	Deep Active Alignment of Knowledge Graph Entities and Schemata	2023	SIGMOD	5.3238057e-05
9,920	Relaxation in Text Search using Taxonomies	2008	VLDB	5.0983269e-05
10,484	AgenticScholar: Agentic Data Management with Pipeline Orchestration for Scholarly Corpora	2026	SIGMOD	4.9605343e-05
10,576	Shape-Agnostic Table Overlap Discovery: A Maximum Common Subhypergraph Approach	2026	SIGMOD	4.9605343e-05

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1	12,729	Web Scale Taxonomy Cleansing	2011	VLDB
2	12,988	Integrating and Querying Taxonomies with QUEST in the Presence of Conflicts	2007	SIGMOD
3	10,604	In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration	2026	SIGMOD
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7	5,283	Using taxonomy, discriminants, and signatures for navigating in text databases	1997	VLDB
8	10,836	LLMs as Stratification Signals for KG Accuracy Evaluation	2026	VLDB
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