IEEE MultiMediaCall for Papers: Special Issue “Multimedia Big Data Analytics in Technology Enhanced Learning” Using digital technologies in teaching and learning has created new challenges for data-based, evidence-driven teaching and learning anal…
CALL FOR PAPERS BigScholar 2017 The 4th WWW Workshop on Big Scholarly Data: Towards the Web of Scholars http://thealphalab.org/bigscholar/A workshop of WWW 2017 (The 26th International World Wide Web Conference) Perth, Australia, April 3-7, 2017 Resear…
Important DatesFull Paper Submissions (8 pages)
* Abstract Submission Deadline: April 27, 2015
* Paper Submission Deadline: May 04, 2015
* Notification of Acceptance: June 05, 2015
* Camera-Ready Paper: July 06, 2015
Poster & Demonstration Submissions (4 pages)
* Submission Deadline: June 22, 2015
* Notification of Acceptance: July 20, 2015
* Camera-Ready Version: August 10, 2015
I-KNOW proceedings will be published by ACM ICPS
Conference Theme: Cognitive Computing and Data-Driven Business
i-KNOW 2015 aims at advancing research at the intersection of disciplines such as knowledge discovery, semantics, information visualization, visual analytics, social (semantic) and ubiquitous computing. The goal of integrating these approaches is to create cognitive computing systems that will interact naturally with humans, learn from their experiences and generate and evaluate evidence-based hypotheses. That is, we interpret cognitive computing as the convergence of various knowledge technologies research fields. On the other hand, data-driven business represents the business perspective on cognitive computing and takes application specific knowledge (such as semantics) into account.
We are specifically interested in the integration of data-centric and user-centric approaches and welcome contributions from both ends of the spectrum.
Conference Topics include (but are not limited to):
Knowledge Discovery & Data Analytics
The growing popularity of big data fostered a new type of researcher, the data scientist. Typical responsibilities of this role are associated with the area of knowledge discovery and data analytics. Algorithmic approaches often focus on machine learning, information retrieval and for textual data on natural language processing. In this call for paper we therefore invite all data scientists to submit your exciting work in the area of knowledge discovery and data analytics. In addition, we also invite (big data) research on application oriented work featuring solid evaluations.
* Big data in knowledge discovery
* Machine learning (e.g. unsupervised, supervised, semi-supervised…)
* Natural language analysis and information extraction
* Data and information retrieval
* Data and pattern mining
* Time series analysis and prediction (e.g. outlier/trend/… detection)
* Open information and relation extraction (e.g. knowledge base population, fact extraction)
* Enterprise information retrieval (e.g. cross-modal, interactive, roles & rights)
* Online methods (e.g. stream processing)
* Text mining (e.g. text summarisation, authorship identification …)
* Diversity & serendipity & privacy (e.g. in recommender systems)
* Deep learning approaches & application
* Text/web/social/user behaviour mining (e.g. sentiment analysis, intent mining …)
* Data mining with taxonomies/ontologies/ linked open data
* Data and information quality
Visual Analytics & Information Visualization
The fields of Visual Analytics, Information Visualization and Knowledge Visualization involve the visual presentation of and interaction with complex knowledge structures, abstract information spaces and large data repositories to facilitate their rapid assimilation and understanding. The objective of this topical block is to bring together researchers and developers as well as practitioners and providers in the field of visualization, to provide an interdisciplinary forum for discussing theoretical and practical results, and to promote research and development in the field. We invite submission of original research papers reporting on theoretical advances, evaluation results or practical applications of Visual Analytics and Information Visualization in relevant real-world scenarios.
* Visual analytics and intelligent user interfaces for data analytics
* Scalability of visual analytics and knowledge discovery techniques
* Interactive knowledge discovery
* Visual representations and metaphors
* Natural interaction techniques for visualization
* Visualization of knowledge, semantic information and linked data
* Visualization of search results, text and multimedia corpora
* Visualization of temporal, spatial and sensory data
* Process and workflow visualization
* Visual support for reasoning and decision making
* Discourse and collaborative visualization
* Cognitive and perceptual factors in visualization
Social networks and social media have profoundly shaped how people interact whilst pushing the boundaries of Web technologies. Social Computing research aims to generate added value from social interactions by harvesting the collective knowledge of groups of people. The Social Computing track at i-Know 2015 particularly invites researchers from multiple disciplines (e.g. Computer Science, Social Sciences) to discuss the following topics:
* 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 and user engagement
* 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 in social computing
Ubiquitous Context-aware Computing
Ubiquitous personal computing devices are key gateways to the world of digital information and to communication; they enable working and learning in times and places where this was previously impossible. This track intends to explore: What has changed due to affordances of these ubiquitous personal technologies? How do interaction concepts need to be re-thought? How to deal with privacy issues or the constant availability of professionals?
We are looking for contributions on interaction experiences, application features, theories for designing ubiquitous computing systems, and evaluations of such systems in the context of business and industry.
* Ubiquitous (collaborative) work, learning, creativitiy??
* Ubiquitous computing architectures and infrastructures?
* Data management in ubiquitous computing systems??
* Bridging the digital and physical worlds?
* Ubiquitous sensors and sensor analytics?
* Usage and usage data analytics?
* User interaction and usability in ubicomp systems, especially in business and industry settings?
* Augmented reality and augmentation interfaces?
* Visual interfaces for collaboration?
* User profiles and user models?
* Context-awareness in ubicomp systems?
* Adaptive systems, applications, interfaces and visualizations?
* Evaluation and measurement approaches?
* Security and privacy aspects of (mobile) sensing applications
Science 2.0 & Open Science
Today scientists are provided with a variety of web-based tools and activities which influence – and may fundamentally change – the way research is carried out. The practice of incorporating such tools and activities in research and scholarly communication is referred to as “Science 2.0” or, broadly spoken, as “Open Science”. The Science 2.0 & Open Science track at the iKnow 2015 particularly invites Web researchers from multiple disciplines (e.g. information science, computer science, sociology, communication and media studies, linguistics, educations studies, legal studies, etc.) to discuss the following topics:
* New publication and research processes and new paradigms for scientific communication
* Opportunities and challenges for researchers and research organizations
* Quality control in Science 2.0/ Open Science (e.g., metadata)
* New indicator systems to measure scientific quality (e.g., altmetrics)
* Epistemology and meaning of Science 2.0- and Open Science-related concepts
* Awareness-support for Science 2.0/ Open Science activities
* New feedback mechanisms among researchers and between science and society
* Empirical studies on the use of social media for Science 2.0/ Open Science as well as use cases
* Marketplaces for scientific data and publications
* Recommender systems in Science 2.0/ Open Science
* Virtual research environments and e-Infrastructures
* Digital research libraries and their role in Science 2.0/ Open Science
* Applications in and for Science 2.0/ Open Science
* Crowd-sourcing in science and citizen science
* Social mining and metadata extraction in academic resources
* Design and architecture of data sharing facilities
* Semantic web standards, data schemes and interoperability formats for Science 2.0/ Open Science
* Challenges in and reservations towards opening up scientific practices and using social media
* Legal dimensions in Science 2.0/ Open Science
* Stefanie Lindstaedt, Know-Center and Graz University of Technology, Austria
* Harald Sack, Hasso-Plattner Institute for IT-Systems Engineering, Germany
* Tobias Ley, Tallinn University, Estonia
Program Chairs Knowledge Discovery, Analytics & Information Visualization
* Jörn Kohlhammer, FHG IGD, Germany (to be confirmed)
* Roman Kern, Know-Center Graz, Austria
* Vedran Sabol, Know-Center Graz, Austria
* Wolfgang Kienreich, Know-Center Graz, Austria
* Christin Seifert, University of Passau, Germany
Program Chairs Social & Ubiquitous Context-aware Computing
* Denis Helic, Graz University of Technology, Austria
* Viktoria Pammer, Know-Center and Graz University of Technology, Austria
* Elisabeth Lex, Know-Center and Graz University of Technology, Austria
* Christoph Trattner, Know-Center Graz, Austria
Program Chairs Science 2.0 & Open Science
* Klaus Tochtermann, ZBW – Leibniz Information Center for Economics, Germany
* Isabella Peters, ZBW – Leibniz Information Center for Economics, Germany
* Peter Kraker, Know-Center Graz, Austria
* Elisabeth Lex, Know-Center and Graz University of Technology, Austria
Poster & Demonstration Chair
* Jörg Simon, Know-Center Graz, Austria
Local Organization & Dissemination Chair
* Nina Simon, Know-Center Graz, Austria
Interactive eBook on ‘Technology-Enhanced Learning for Big Data Skills Development’ *** Call for contributions *** *Rationale* “Data is at the centre of the future knowledge economy and society“, the European Commission predicts (EC, 2014, p.4) and for the Big Data economy to flourish, “an adequate skills base” in form of a “sufficient number of domain […]