The I-Know 2017 - 17th International Conference on Knowledge Management and Knowledge Technologies is dedicated to various aspects of knowledge management, including:
- KNOWLEDGE MANAGEMENT
- Mobile Work and Performance Support
- Enterprise 2.0 and Corporate Web 2.0
- Personal Information Management
- Creativity and Knowledge Work
- Open Innovation and Crowd Funding
- Innovative Business Models
- Knowledge Transfer and Experience Management
- Innovation Process and Knowledge Maturing
- Increasing Efficiency and Measurement Approaches
- Process-oriented Knowledge Management
- Skill and Competency Management
- Convergence of Knowledge Management and Learning
- Trust & Privacy Approaches
- Service-oriented Architectures and Knowledge Infrastructures
- MOBILE COMPUTING
- Bridging the Digital and Physical Worlds
- Mobile and Ubiquitous Data Management and Processing
- Usage and Usage Data Analytics
- Sensors and Sensor Analytics
- Mobile Work (requirements, characteristics, solutions…)
- Mobile Social Networking and Mobile Web
- Ubiquitous Computing Architectures and Infrastructures
- Context-aware Systems and Applications
- Security and Privacy Aspects of (mobile) Sensing Applications
- User Interaction and Usability on Mobile Devices
- SOCIAL COMPUTING
- Web 2.0, Future Internet, and Web Science
- Social Media, Social Web, and Social Network Analysis
- Information Quality and Knowledge Maturing
- Collaborative Knowledge Creation and Crowdsourcing
- Social Information Seeking and Recommender Systems
- Community Evolution
- Temporal and Spatial Analysis of Social and Information Networks
- Social Search and Retrieval Systems
- Semantic Uplifting in Social Networks
- Social-Semantic-Content Networks and their Analysis
- Social Gaming and Human Computing
- Spam, Misinformation and Malicious Activity Discovery in Social Systems
- Privacy & Trust
- SCIENCE 2.0
- Opportunities and Challenges for Researchers and Research organizations
- New Publication and Research Processes
- Awareness-support for Science 2.0 Activities
- New Indicator Systems to Measure Scientific Quality
- New Feedback Mechanisms among Researchers and between Science and Society
- New Paradigms for Scientific Communication
- Marketplaces for Scientific Data and Publications
- Empirical Studies on the Use of Web 2.0 Tools for Science 2.0
- Virtual Research Environments
- Recommender Systems in Science 2.0
- Applications in and for Science 2.0
- Digital Research Libraries
- Robust Methods for dealing with Noisy Crowd-sourced Data
- Crowd-sourcing in Science
- Social Mining and Metadata Extraction in Academic Resources
- Data Schemes and Interoperability Formats
- Design and architecture of data sharing facilities
- Metadata Quality and Quality Assessment
- Systems design accounting for standardized data sets
- Semantic Web Standards for Science 2.0
- KNOWLEDGE DISCOVERY & DATA MINING
- Data Mining in the Linked Data Cloud
- Big Data in Knowledge Discovery
- Unsupervised Machine Learning
- Text/Web/Social/User Behaviour Mining
- Deep Machine Learning
- Supervised and Semi-Supervised Learning
- Temporal Knowledge Discovery
- Enterprise Retrieval
- Natural Language Analysis and Sentiment Detection
- Data Structures, Frameworks, and Models underlying Knowledge and Data Mining
- Data and Information Quality
- Data and Information Retrieval (e.g. cross-language retrieval, interactive retrieval methods, multimedia and cross-modal information retrieval)
- Knowledge Base Population and Information Extraction
- VISUAL ANALYTICS & INFORMATION VISUALISATION
- Information Visualisation
- Visual Analytics and Intelligent User Interfaces for Data Analytics
- Interactive Knowledge Discovery
- Scalability of Visual Analytics and Knowledge Discovery Techniques
- Visualisation of Knowledge, Semantic Information and Linked Data
- Visual Representations and Interaction Techniques
- Visualisation of Temporal, Spatial and Sensory Data
- Visualisation of Search Results, Text and Multimedia Corpora
- Visual Support for Reasoning and Decision Making
- Process and Workflow Visualisation
- Cognitive and Perceptual Factors in Visualization
- Discourse and Collaborative Visualisation
Who should Attend
Researchers and developers from various knowledge management disciplines.
