The Data Science and Information Systems (Dainfos) Lab focuses on large-scale data management and data-driven analytics by conducting fundamental and cutting-edge research in databases, data mining, machine learning, Web mining, information retrieval, and natural language processing.
Our Goals and Speciality
Our goals: designing efficient and scalable algorithms, making sense of data for data-intensive applications. The following lists the research areas with applications that we are focusing currently:
Data mining and machine learning algorithms
– social networks mining, data integration, and analysis
– multi-core parallel algorithms
– distributed algorithms
– randomization and approximation
– data simplification and summarization
– data visulization
– graph mining, tensor-based methods
– other methods
– applications: any data mining tasks including marketing, data visulization, outlier detection, recommendation, OLAP, etc.
Query processing and Searching
– building search engines
– textual and image/multimedia data retrieval
– data ranking
– entity recognition
– data integration
– query expression
– streaming/complex event processing
– applications: search engine, business process management, model verification, etc.
– smart routing algorithms
– listing and selection
– applications: Logistics, transportation, supply chain, production, etc.
Spatio-temporal data management
– data indexing
– data compression
– 3D modeling, 2D/3D data visualization
– data warehouse
– applications: mobility analysis, mobile advertising, moving objects, mapping, etc.
Data privacy and protection
– query preserved data encryption
– data sharing
– cloud data management
– graph data protection
– applications: cloud computing, social networks, etc.