ScholarWorks@Sookmyung Women's University: Lee, Ki Yong

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Lee, Ki Yong (이기용)

공과대학 (소프트웨어학부(첨단))

Research Area: 컴퓨터시스템 소프트웨어, 응용 소프트웨어, 인공지능

Tel 02-2077-7583
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MapReduce:4||Word2vec:3||Big Data:3||WWW:3||맵리듀스:3||데이터 스트림:3||OLAP:3||Data Streams:3||LSTM 오토인코더:3||ORB:2||Flash memory:2||Sensor network:2||IoT:2||배열 데이터:2||mobile devices:2||Outlier detection:2||Anomaly Detection:2||빅데이터:2||Mulitway Stream Window Join:2||deep clustering:2||Simulation:2||Hash Join:2||LSTM Autoencoder:2||LSTM autoencoder:2||B+tree:2||다중 질의 최적화:2||Query Processing:2||Internet of Things:2||Query processing:2||Load Shedding:2||Request distribution:2||index structure:2||SIFT:2||연속 조인 질의:2||spatiotemporal index:2||storage systems:2||SURF:2||Dynamic Time Warping:1||Electric Scooter Sharing Service:1||Embedded DBMS:1||Ensemble Method:1||Eventdetection:1||Explainable Artificial Intelligence:1||Finding Similar Regions:1||Flashbased DBMS:1||Gait Analysis:1||Game Log Data:1||Gradient Boosting:1||Gradientbased Explanation:1||Graph Convolutional Network:1||Graph Embedding:1||Graph Neural Network:1||Graph Similarity:1||Graph anomaly detection:1||Graph neural network (GNNs):1||Groupby 질의:1||Hierarchical Classification:1||Human Classification:1||Human gait:1||Innetwork join:1||Index Update:1||Index structure:1||Indexes:1||Information technology and system:1||Inverted Index:1||IoT data:1||Keyword Search:1||Kinect:1||LSTM classifier:1||Levenshtein Distance:1||Limit Order Book:1||Load shedding:1||MLC NAND flash memory:1||Materialized view:1||Meta Pseudo Label:1||Multiquery optimization:1||Multiway stream join:1||Multimedia CE Device:1||Multimedia system:1||Multiple Skyline Queries:1||Multiple skyline query:1||NAND flash memory:1||News:1||Object Detection:1||Ontology Structured Query Ranking:1||Ontology Triple Pattern Affinity:1||Outlier region:1||Partitioning algorithms:1||Photo Recognition:1||Platforms:1||Positional encoding:1||Product Taxonomy:1||Provenance:1||Purchase History:1||Query Stream:1||Raspberry Pi:1||RealTime Analysis:1||SQL:1||Semantic Web:1||SemiSupervised Learning:1||Sequence:1||Sequence Similarity:1||Sequence Similarity Measure:1||Sequence prediction:1||Sessionbased Recommendation:1||Similarity Measure:1||Simulation Result Prediction:1||Simulation prediction:1||Simulation service:1||Sliding window:1||Social Bookmarks:1||Spatial database:1||Spatiotemporal join:1||Statistical Machine Learning:1||Stock Price Prediction:1||Stream Data Mining:1||Stream processing:1||Systems:1||Tag:1||Taxonomy:1||Textual database:1||Threedimensional displays:1||Time Normalization:1||Time measurement:1||Timeinterval association rule:1||Timestamped sequences:1||Topk:1||Trajectory Data Stream:1||Transaction Data Analysis:1||Transaction processing:1||Transformer:1||TwoDimensional array:1||Urban environmental sensing data:1||Visually Impaired:1||Web cache:1||Web page similarity:1||Weighted Graph:1||Weighted Graph Embedding:1||Wireless sensor network:1||YOLO:1||anomalous sequence detection:1||approximate query processing:1||array data:1||big data:1||buffer sharing:1||cache admission control:1||classification:1||clustered video server:1||continuous join query:1||contrastive learning:1||data augmentation:1||data mining:1||data publication:1||deep learning:1||dynamic topic modeling:1||dynamic workload:1||energyefficient:1||filtering:1||geographic information systems:1||graph autoencoder:1||graph embedding:1||graph neural network:1||graph neural networks:1||graph node clustering:1||graph similarity:1||groupby query:1||hierarchical classification:1||kNN classifier:1||kNN query:1||kanonymity:1||kmeans:1||kmeans clustering:1||k평균 클러스터링:1||machine learning:1||mesh join:1||multiple query optimization:1||naturebased solutions:1||node clustering:1||node embedding:1||outlier:1||outlier detection:1||outlier region detection:1||outlying region discovery:1||privacy:1||purchase history:1||realtime data warehouse:1||research trend:1||sequence similarity:1||sharing loss:1||similarity measure:1||simulation result prediction:1||simulation result reuse:1||simulation service system:1||smart city:1||social network:1||spatial database:1||spatiotemporal join:1||thing data:1||time series:1||weighted graph:1||가중 그래프:1||계층적 분류체계:1||공유 손실:1||구매 이력:1||구매이력 데이터 분석:1||궤적 데이터 스트림:1||그래프 노드 클러스터링:1||그래프 신경망:1||그래프 오토인코더:1||그래프 유사도:1||그래프 임베딩:1||뉴스:1||다중 스카이라인 질의:1||다중 스트림 윈도우 조인:1||대조 학습:1||데이터 마이닝:1||데이터 스트림 마이닝:1||데이터 증강:1||데이터 큐브:1||도시 환경 센싱 데이터:1||동반 그룹 탐색:1||동적 데이터 웨어하우스:1||동적 작업부하:1||동적 타임 워핑:1||딥 클러스터링:1||딥러닝:1||라즈베리 파이:1||레벤슈타인 거리:1||로그 블록 로깅:1||메쉬 조인:1||메타 의사 라벨:1||모바일 장치:1||무선 센서 네트워크:1||배열 데이터베이스:1||배열 질의 처리:1||버퍼 공유:1||부하감소:1||분류:1||사물 데이터:1||상품 분류 체계:1||색인 갱신:1||색인구조:1||소셜 북마크:1||스마트시티:1||시각장애인:1||시계열 데이터:1||시공간 색인:1||시공간 조인:1||시맨틱 웹:1||시뮬레이션:1||시뮬레이션 결과 예측:1||시퀀스:1||시퀀스 유사도:1||시퀀스 유사도 측정:1||실시간 데이터 웨어하우스:1||실시간 분석:1||아웃라이어:1||역색인:1||연속 질의:1||오토인코더:1||온톨로지 구조 질의 랭킹:1||온톨로지 트리플 패턴 연관도:1||요청 분배:1||웹 페이지 간 유사도:1||유사 구역 탐색:1||유사도 측정:1||이상 구역 탐색:1||이상 시퀀스 탐지:1||이상 탐지:1||이상치 탐색:1||이상치 탐지:1||저장시스템:1||주가예측:1||준지도 학습:1||지폐 인식:1||질의 스트림:1||질의 처리:1||집계 질의:1||클러스터 비디오 서버:1||키워드 검색:1||태그:1||통계적 기계학습:1||특이 구역 탐색:1||플래시 메모리:1||플래시 메모리 기반 데이터베이스:1||합성곱 신경망:1||해시 조인:1||2dimensional array analysis:1||호가창:1||Active data warehouse:1||Adaptive query processing:1||Aggregate Query:1||Aggregate query:1||Array Data:1||Array Database:1||Array Query Processing:1||Arrival order pattern:1||Association rule mining:1||Attention Mechanism:1||Autoencoder:1||B+트리:1||Banknote Recognition:1||Browsing State Recovery:1||Buffering:1||CNN:1||Category information:1||Classification:1||Clustered VOD system:1||Collective outliers:1||Companion Groups Detection:1||Continuous Join Query:1||Continuous Queries:1||Continuous query:1||DForest:1||Data Analysis:1||Data Cube:1||Data cube:1||Data stream:1||Data warehouse:1||Datadriven simulation:1||Database:1||Database management:1||Deep Learning Model Optimization Regression Model Time Lag:1||Depth Camera:1||Distributed data stream:1||

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Sookmyung Women's University. Cheongpa-ro 47-gil 100 (Cheongpa-dong 2ga), Yongsan-gu, Seoul, 04310, Korea02-710-9127

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