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이종욱
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데이터마이닝 추천시스템 정보검색 자연어처리 심층신경망 기계학습
관심분야
데이터마이닝 데이터베이스 추천시스템 정보검색 및 웹 마이닝
학력
- (Ph.D.) 2012 포항공과대학교 컴퓨터공학과
- (B.S.) 2006 성균관대학교 정보통신공학부
약력/경력
- 2016.09 – 현재 성균관대학교 소프트웨어학과 교수
- 2014.09 – 2016.08 한국외국어대학교 컴퓨터공학과 교수
- 2012.12 – 2014.8 The Pensylvania State University, 박사 후 연구원
- 2012.03 – 2014.11 포항공과대학교, 박사 후 연구원
학술지 논문
- (2023) Your lottery ticket is damaged: Towards all-alive pruning for extremely sparse networks. INFORMATION SCIENCES. 634
- (2023) CoMix: Collaborative filtering with mixup for implicit datasets. INFORMATION SCIENCES. 628
- (2022) Large-scale tucker Tensor factorization for sparse and accurate decomposition. JOURNAL OF SUPERCOMPUTING. 78, 16
- (2022) DeepTESR: A Deep Learning Framework to Predict the Degree of Translational Elongation Short Ramp for Gene Expression Control br. ACS SYNTHETIC BIOLOGY. 11, 5
- (2022) Knowledge distillation meets recommendation: collaborative distillation for top-N recommendation. KNOWLEDGE AND INFORMATION SYSTEMS. 64, 5
- (2021) Distilling from professors: Enhancing the knowledge distillation of teachers. INFORMATION SCIENCES. 576, 1
- (2021) Optimizing Read Operations of Hadoop Distributed File System on Heterogeneous Storages. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING. 37, 3
- (2019) CrowdStart: Warming up cold-start items using crowdsourcing. EXPERT SYSTEMS WITH APPLICATIONS. 138, 1
- (2018) Crowdsourced promotions in doubt: Analyzing effective crowdsourced promotions. INFORMATION SCIENCES. 432, 1
- (2017) CrowdK: Answering top-k queries with crowdsourcing. INFORMATION SCIENCES. 399, 1
- (2017) l-Injection: Toward Effective Collaborative Filtering using Uninteresting Items. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. PP, 99
- (2016) Optimizing skyline queries over incomplete data. INFORMATION SCIENCES. 361, 1
- (2016) Improving the accuracy of top-N recommendation using a preference model. INFORMATION SCIENCES. 348, 1
학술회의논문
- (2022) Long-tail Mixup for Extreme Multi-label Classification. ACM Conference on Information and Knowledge Management. 미국
- (2022) SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval. ACM Conference on Information and Knowledge Management. 미국
- (2022) Logit Mixing Training for More Reliable and Accurate Prediction. International Joint Conference on Artificial Intelligence. 미국
- (2022) Bilateral Self-unbiased Learning from Biased Implicit Feedback. ACM SIGIR Conference on Information Retrieval. 대한민국
- (2022) 세션 기반 추천의 반복 및 비반복 항목 예측에 대한 성능 비교 및 분석. 2022 한국컴퓨터종합학술대회. 대한민국
- (2022) 의사 문장 표현을 활용한 수학 문장형 문제 풀이 모델. 2022 한국컴퓨터종합학술대회. 대한민국
- (2022) 지식 추적 모델의 정확도 개선을 위한 양자화된 정답률 임베딩 방법. 2022 한국컴퓨터종합학술대회. 대한민국
- (2022) FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation. International Conference on Management of Data. 미국
- (2022) S-Walk: Accurate and Scalable Session-based Recommendation with Random Walks. ACM International Conference on Web Search and Data Mining. 미국
- (2021) Dual Unbiased Recommender Learning for Implicit Feedback. ACM SIGIR Conference on Information Retrieval. 미국
- (2021) Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation. Conference on Computer Vision and Pattern Recognition. 미국
- (2021) MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 미국
- (2021) Session-aware Linear Item-Item Models for Session-based Recommendation. International World Wide Web Conference. 미국
- (2021) Local Collaborative Autoencoders. ACM International Conference on Web Search and Data Mining. 미국
- (2020) Bridging the Gap between Click and Relevance for Learning-to-Rank with Minimal Supervision. ACM Conference on Information and Knowledge Management. 아일랜드
- (2020) 임베딩 드롭아웃을 활용한 세션 기반 신경망 추천 모델의 성능 개선. 한국컴퓨팅종합학술대회. 대한민국
- (2020) Decoupled Word Embeddings using Latent Topics. ACM/SIGAPP Symposium on Applied Computing. 체코
- (2020) Diversity Regularized Autoencoders for Text Generation. ACM/SIGAPP Symposium on Applied Computing. 체코
- (2019) Collaborative Distillation for Top-N Recommendation. IEEE International Conference on Data Mining. 중국
- (2019) Characterization and Early Detection of Evergreen News Articles. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 독일
- (2019) Dual Neural Personalized Ranking. World-Wide Web Conference. 미국
- (2018) 자연어 기반 SQL문 생성을 위한 칼럼 예측 모델. 한국정보과학회 학술발표논문집. 대한민국
- (2018) 한글 자연어 처리를 위한 빈도수 기반 음절 임베딩. 한국정보과학회 학술발표논문집. 대한민국
- (2017) 다차원 공간에서 정확한 선형 스카이라인 알고리즘. 2017 한국소프트웨어종합학술대회. 대한민국
- (2017) 중첩 그룹과 이상치 탐지를 고려한 스펙트럴 군집 알고리즘. 한국 데이터베이스 학회. 대한민국
- (2017) IDAE: Imputation-boosted Denoising Autoencoder for Collaborative Filtering. ACM Conference on Information and Knowledge Management. 싱가포르
- (2017) IDAE: Imputation-boosted Denoising Autoencoder for Collaborative Filtering. International Conference on Information and Knowledge Management. 싱가포르
- (2016) "Told you i didn't like it": Exploiting uninteresting items for effective collaborative filtering. 32nd IEEE International Conference on Data Engineering (ICDE). 핀란드
- (2016) Analyzing Crowdsourced Promotion Effects in Online Social Networks. 31st Annual {ACM} Symposium on Applied Computing (SAC). 이탈리아
- (2016) CrowdSky: Skyline Computation with Crowdsourcing. the 19th International Conference on Extending Database Technology (EDBT). 프랑스