Data Mining Lab.
Welcome to Data Mining Laboratory in the Department of Computer Science and Engineering at Seoul National University. Our research interests lie in artificial intelligence (AI), data mining, and machine learning to find models, algorithms, and systems for data analysis. Specifically, we focus on the following research topics: deep learning & machine learning, recommender & QA systems, graphs/tensors, and financial AI.
What's New
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[Feb. 2025] 2 papers accepted to PAKDD 2025, a top tier data mining conference.
2 papers from Data Mining Lab are accepted to PAKDD 2025, a top tier data mining conference. Congratulations!
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[Jan. 2025] A paper accepted to ICLR 2025, a top tier AI conference.
A paper accepted to ICLR 2025, a top tier AI conference. The paper “SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning” proposed SynQ, an accurate zero-shot quantization method applicable to any existing methods that fine-tune with synthetic datasets.
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[Dec. 2024] A paper accepted to AAAI 2025, a top tier AI conference.
A paper accepted to AAAI 2025, a top tier AI conference. The paper “Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning” proposed PULL, an accurate link prediction method in edge-incomplete graphs.
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[Oct. 2024] 3 papers accepted to BigData 2024, a top tier data mining conference.
3 papers from Data Mining Lab are accepted to BigData 2024, a top tier data mining conference. Congratulations!
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[Oct. 2024] A paper accepted to WSDM 2025, a top tier data mining conference.
A paper is accepted to WSDM 2025, a top tier data mining conference. The paper "Sequentially Diversified and Accurate Recommendations in Chronological Order for a Series of Users " proposed a reranking method that diversifies the recommendation results based on items' potential exposure opportunities.