Over the past 20 years, data has increased in a large scale in various fields. Hundreds of Petabyte are generated every day by industries, Internet companies, medias and social networks. This explosive increase of big masses of structured and unstructured data need more real-time analysis which challenges the existing traditional analytic tools. The exponential growth of organizations’ needs for data analysis for Business Intelligence purposes and Knowledge management requires more sophisticate tools. However, it impossible to perform any kind of exploratory or analysis on this Big amount of data by using desktop or non-parallel tools. Hence, the needs for developing of new technologies, methods and algorithms for Big data generation, acquisition, storage and analysis.
This track provides a forum for researchers, practitioners, developers, and users to explore and share the latest results, approaches, techniques, concepts, and technologies in Big Data, Business Intelligence, IR knowledge management, and Data Analytics.
Foundational Models for Big Data
Computational Modeling for Big Data
Algorithms and Programming Techniques for Big Data Processing
Big Data Analytics and Metrics
Decision making in social and mobile network Big Data
Large-scale Recommendation and Social Media Systems
Privacy Preserving Big Data Analytics
Anomaly Detection in Very Large Scale Systems
Collaborative Threat Detection using Big Data Analytics
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Machine learning based on Big Data
Visualization Analytics for Big Data
Big Data Economics
Real-life Case Studies of Value Creation through Big Data Analytics
Scientific Applications of Big Data
Information Retrieval models
Text representation, Query models, Query Languages, Query Processing
Novel IR Interfaces (Exploratory, Interactive, Accessible)
Semantic search (entity-based IR, Linked data)
Collaborative, Crowd-Based, and Game-Based Approaches to IR
Context-based IR (mobile search, Click Models, Interaction Models)
Personalization, Recommendation, Advertising, and Search
Aggregation (Summarization, Clustering, Integration), Classification
Information Extraction and Filtering
Social Media and Social Networks (analysis, management, search)
Spatial, Temporal, and Graph Data (analysis, management, search)
Time-Sensitive and Real-time Search
Graph, Semantics, Web, Management
Applications (in Business and science)
11月29日
2016
12月02日
2016
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