13th International Conference on Knowledge Management and Knowledge Computing
4 - 6 September 2013, Graz, Austria
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Synergies of Knowledge Disciplines
The 13th International Conference on Knowledge Management and Knowledge Computing (I-KNOW 2013) will be held from September 4 to 6, 2013 at the Messe Congress in Graz, Austria. I-KNOW is a top-tier international conference in the areas of knowledge management and knowledge computing. Since 2001, it has successfully brought together leading researchers and developers from the these communities and attracted annually over 500 international attendees.
The purpose of the conference is to provide a crystallization point for different disciplines of knowledge management (such as Business Science and the Social Sciences) and knowledge computing (such as knowledge discovery, social networks and context-aware computing). Renown researchers from these knowledge disciplines meet to identify challenging problems facing the development and introduction of future knowledge systems, and to shape future research directions through the publication of high quality, applied and theoretical research findings.
I-KNOW 2013 will continue the successful tradition of the conference series and will specifically provide interactive and innovative formats to support the synergies of knowledge management and knowledge computing fields. We encourage submissions of high quality papers on all topics in the general areas of knowledge & data analytics, social & ubiquitous computing, knowledge & innovation management, and science 2.0.
Based on successful collaboration, I-KNOW 2013 will continue the tradition of collocating with the I-SEMANTICS conference, the 9th International Conference on Semantic Systems (www.i-semantics.at<http://
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Important Dates
Full Paper Submissions
* Abstract Submission Deadline: March 25, 2013
* Paper Submission Deadline: April 1, 2013
* Notification of Acceptance: May 3, 2013
* Camera-Ready Paper: June 10, 2013
Poster & Demonstration Submissions
* Submission Deadline: May 21, 2013
* Notification of Acceptance: June 18, 2013
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Conference Topics
Knowledge & Data Analytics
I-KNOW 2013 seeks for novel contributions in advancing the field of knowledge & data analytics as well as in providing new means to utilize, navigate and search large, heterogeneous data pools. We aim to bridge data-centric and user-centric approaches and welcome contributions from both ends of the spectrum. Besides new algorithms and techniques, we are also interested on applications in the wild, user-centric evaluations of real-world applications as well as empirical studies. Topics of interest include (but are not limited to):
Knowledge Discovery & Data Mining
* Big Data in Knowledge Discovery
* Data Mining in the Linked Data Cloud
* Text/Web/Social/User Behaviour Mining
* Unsupervised Machine Learning
* Supervised and Semi-Supervised Learning
* Deep Machine Learning
* Enterprise Retrieval
* Temporal Knowledge Discovery
* Data Structures, Frameworks, and Models underlying Knowledge and Data Mining
* Natural Language Analysis and Sentiment Detection
* Data and Information Retrieval (e.g. cross-language retrieval, interactive retrieval methods, multimedia and cross-modal information retrieval)
* Data and Information Quality
* Knowledge Base Population and Information Extraction
Visual Analytics & Information Visualisation
* Visual Analytics and Intelligent User Interfaces for Data Analytics
* Information Visualisation
* Scalability of Visual Analytics and Knowledge Discovery Techniques
* Interactive Knowledge Discovery
* Visual Representations and Interaction Techniques
* Visualisation of Knowledge, Semantic Information and Linked Data
* Visualisation of Search Results, Text and Multimedia Corpora
* Visualisation of Temporal, Spatial and Sensory Data
* Process and Workflow Visualisation
* Visual Support for Reasoning and Decision Making
* Discourse and Collaborative Visualisation
* Cognitive and Perceptual Factors in Visualization
Social & Ubiquitous Computing
I-KNOW 2013 seeks for innovative contributions in the fields of social and ubiquitous computing, specifically with the focus on supporting to mobile knowledge work. We aim at developing deeper insights into the mechanisms of collaborations, communities, content quality, etc. - not only based on user behaviour in virtual environments but also in the real world. The currently open challenge is, to technically deal with behaviour and usage data and to analyse it in such a way as to benefit the individual in highly distributed and mobile situations at work and in personal tasks, such as in health care and crisis settings as well as in community engagements and self-directed learning. Besides new apps, methods, and architectures, we are also interested on applications in the wild, user-centric evaluations of real-world applications as well as conceptual overviews that help us understand - or challenge our understanding of - the impact of these technologies.
Topics of interest include (but are not limited to):
Social Computing
* Social Media, Social Web, and Social Network Analysis
* Web 2.0, Future Internet, and Web Science
* Collaborative Knowledge Creation and Crowdsourcing
* Information Quality and Knowledge Maturing
* Community Evolution
* Social Information Seeking and Recommender Systems
* Social Search and Retrieval Systems
* Temporal and Spatial Analysis of Social and Information Networks
* Social-Semantic-Content Networks and their Analysis
* Semantic Uplifting in Social Networks
* Spam, Misinformation and Malicious Activity Discovery in Social Systems
* Social Gaming and Human Computing
* Privacy & Trust
Ubiquitous Computing
* Mobile and Ubiquitous Data Management and Processing
* Bridging the Digital and Physical Worlds
* Sensors and Sensor Analytics
* Usage and Usage Data Analytics
* Mobile Social Networking and Mobile Web
* Mobile Work (requirements, characteristics, solutions...)
* Context-aware Systems and Applications
* Ubiquitous Computing Architectures and Infrastructures
* User Interaction and Usability on Mobile Devices
* Security and Privacy Aspects of (mobile) Sensing Applications
Knowledge Management in Industry & Science
Like all major societal challenges, knowledge management touches diverse aspects of life and thus needs a multi-disciplinary approach for finding solutions. We seek for novel contributions from management science, social sciences, psychology and computer science which address the challenges of managing knowledge in increasingly distributed and mobile work settings as well as turning knowledge into high impact innovations. We will examine these topics within enterprise and the scientific settings. Besides new theories, models and approaches, we are also interested on applications in the wild, user-centric evaluations of real-world applications as well as empirical studies. Topics of interest include (but are not limited to):
Knowledge Management
* Enterprise 2.0 and Corporate Web 2.0
* Mobile Work and Performance Support
* Creativity and Knowledge Work
* Personal Information Management
* Innovative Business Models
* Open Innovation and Crowd Funding
* Innovation Process and Knowledge Maturing
* Knowledge Transfer and Experience Management
* Process-oriented Knowledge Management
* Increasing Efficiency and Measurement Approaches
* Convergence of Knowledge Management and Learning
* Skill and Competency Management
* Service-oriented Architectures and Knowledge Infrastructures
* Trust & Privacy Approaches
Science 2.0
* New Publication and Research Processes
* Opportunities and Challenges for Researchers and Research organizations
* New Indicator Systems to Measure Scientific Quality
* Awareness-support for Science 2.0 Activities
* New Paradigms for Scientific Communication
* New Feedback Mechanisms among Researchers and between Science and Society
* Empirical Studies on the Use of Web 2.0 Tools for Science 2.0
* Marketplaces for Scientific Data and Publications
* Recommender Systems in Science 2.0
* Virtual Research Environments
* Digital Research Libraries
* Applications in and for Science 2.0
* Crowd-sourcing in Science
* Robust Methods for dealing with Noisy Crowd-sourced Data
* Data Schemes and Interoperability Formats
* Social Mining and Metadata Extraction in Academic Resources
* Metadata Quality and Quality Assessment
* Design and architecture of data sharing facilities
* Semantic Web Standards for Science 2.0
* Systems design accounting for standardized data sets
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