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ENIC 2016 : The Third European Network Intelligence Conference


When Sep 5, 2016 - Sep 7, 2016
Where Wrocław, Poland
Submission Deadline Jun 3, 2016
Notification Due Jul 4, 2016
Final Version Due Jul 11, 2016
Categories    social networks   social network analysis   artificial intelligence   machine learning

Call For Papers

Dear Sir/Madame,
It is our pleasure to invite you to conference European Network Intelligence Conference (ENIC), September 5-7, 2016, Wroclaw, Poland –
Please find the details of the conference below.

We are more and more surrounded by different kinds of networks, interconnected systems and vast amounts of interrelated data. Various web collaborative portals, blogs, wikis, video publishing services (youtube), e-commerce sites (eBay), social networking sites (Facebook) sensor networks, smart phones users exchanging multimedia as well as IT systems collaborating with one another in most organisations are a good example of networks that require new adequate analytical methods.
The aim of the annual European Network Intelligence Conference (ENIC) is to create an open premier forum to exchange knowledge and experience as well as to discuss recent advances, theories, and techniques related to both various types of networks and intelligent, analytical, computational methods.
Every edition of the conference will focus on only a few selected more specific scientific domains - tracks. The third event will include five such areas:
1. Social network and social media analysis,
2. Intelligent Methods for Optimization of Communication Networks,
3. Compound Methods of Pattern Classification,
4. Interaction Studies and Semantic Communication,
5. Intelligent Techniques in Video and Document Analysis.
The tracks will bring together the research groups from the specified disciplines, along with many of the e-commerce companies interested in applications of the intelligent tools in their products. The track will enable researchers and practitioners to present their latest research and identify challenges in recommendation systems. The special interest will be focused on the design cooperation platform for academia and industry.
Initially, the conference will be led and hosted by the ENGINE Centre and partner organisations and substantially supported by the Seventh Framework Programme. However, we hope to create a wider active ENIC community for the future
Since ENIC 2016 is sponsored by the ENGINE Project, one author for each paper will be registered free of charge. The ENGINE Centre will cover their participation, proceedings costs, coffee brakes and banquet but only if they will present in person their accepted paper during the conference. It does not include travel and accommodation costs.

Key dates
Full paper submission deadline: June 3, 2016 (extended deadline)
Notification of acceptance: July 4, 2016
Camera-ready papers due: July 11, 2016
Conference: September 5-7, 2016 (Monday - Wednesday)
Keynote Speakers

ENIC 2016 Tracks
1. Social network and social media analysis (SNA / SMA)
Track Chairs:
• Henric Johnson, Blekinge Institute of Technology, Sweden
• Piotr Bródka, Wrocław University of Technology, Poland
• Reda Alhajj, University of Calgary, Canada
• Przemysław Kazienko, Wrocław University of Technology, Poland
Social network and social media analysis have experienced tremendous advances within the last few years due to the increasing trends towards users interacting with each other in online social networks such as Facebook or Twitter etc. Also, these networks are organized as graphs, and the data on social networks and social media requires new methods to perform network and data analysis. This track will enable researchers and practitioners to present their latest research and identify challenges. The track solicits theoretical and experimental findings along with their real-world applications. This announcement further solicits original contributions of high-quality research in, but not limited to, the following topics:
• Application of social network and social media analysis
• Big data approach SNA / SMA
• Blog and microblog analysis
• Collaborative query processing and optimization
• Community discovery and analysis in large scale social networks
• Contextual social network analysis
• Crowd sourcing
• Cultural, anthropological and political aspects in SNA / SMA
• Data acquisition and social relationship extraction for SNA/SMA
• Data integration and identification in SNA / SMA
• Data models for social networks and social media
• Data protection and security issues in SNA / SMA
• Deep web SNA / SMA
• Dynamics of networks and social communities
• Dynamics and patterns in social media data
• Economic impact of social network discovery
• Efficiency in SNA / SMA
• Evaluation of SNA / SMA
• Evolution of social networks and social media
• Exchange networks
• Graph-based algorithms for SNA/SMA
• Impact of social networks on recommendations systems
• Information diffusion and spread of influence in social networks
• Knowledge networks
• Large graph and parallel processing
• Machine learning methods for SNA / SMA
• Measures, similarity and dissimilarity in SNA / SMA
• Multi-agent based social network and social media modelling and analysis
• Multiple / multilayer social network analysis
• Multiple social network interaction and multiple media system correlation
• Outlier and misbehaviour detection in SNA/SMA
• Pattern discovery on the web data and in large organizations
• Personalization in social services (overlaps the second track)
• Privacy and security in SNA / SMA
• Reasoning fort social and media data
• Recommender systems in establishment of social relations
• Scalability of social networking, search algorithms and social media data processing
• Sentiment analysis
• Signed graphs and multigraphs in SNA / SMA
• Simulations and computational models for social networks
• Social intelligence
• Social role identification
• Social search analysis
• Spatial networks
• Statistical modelling of large networks
• Trust networks and evolution of trust
• Visual representation of dynamic social networks and social media evolution
• Wikipedia-based data analysis

2. Intelligent Methods for Optimization of Communication Networks (IMOCN)
Track Chairs:
• Krzysztof Walkowiak, Wrocław University of Technology, Poland
Recent developments in communications and networking technologies have reached an unprecedented level, however still many new challenges and opportunities are emerging. Starting from the physical layer with new approaches of Elastic Optical Network, 5G mobile, MANET and VANET technologies up to recent ideas in higher network layers including software defined networks (SDN) and network function virtualization (NFV) trigger the need to deploy new intelligent methods to optimize the network resources. Among the most vital optimization goals for communication networks of various types, the following must be enumerated: OPEX costs, CAPEX costs, energy efficiency, scalability, delay, survivability, security.
To ensure complete coverage of the advances in field, the Intelligent Methods for Optimization of Communication Networks track solicits original contributions in, but not limited to, the following topics:
• Combinatorial and metaheuristics algorithms for optimization of communication networks
• Graph theory
• Elastic Optical Networks
• Optical network architectures, design and performance evaluation
• Mobile networking, mobility and nomadicity
• 5G networks
• Internet of Things (IoT)
• Machine-to-Machine (M2M) communications
• Wireless mesh networks
• Vehicular ad hoc networks (VANETs)
• Congestion and admission control
• Future Internet and next-generation networking architectures
• Software Defined Networking (SDN)
• Overlay networks
• Peer-to-peer networks
• Cloud computing
• Anycast routing
• Multicast routing
• Content-oriented networks
• Network survivability and resilience
• Intrusion and attack detection/prevention
• Multi-layer networks,
• Energy efficiency

3. Compound Methods of Pattern Classification (CMPC)
Track Chairs:
• Michał Woźniak, Wrocław University of Technology, Poland
• Bogusław Cyganek, AGH University, Poland
• Bartosz Krawczyk, Wrocław University of Technology, Poland
Compound Pattern Classification attempts to enhance the performance of systems (clustering, classification, prediction, feature selection, preprocessing, data balancing, rule extraction, etc.) by using multiple or hybrid models instead of using a single one. This approach is intuitively meaningful as a single model may not always be the best for solving a complex problem while multiple models are more likely to yield results better than each of individuals. The aim of this track is to discuss the new theoretical trends and the applications of pattern classification and related approaches. To ensure complete coverage of the advances in field the track will cover the following topics:
• Ensemble clustering
• Ensemble classifiers
• Ensemble methods for regression, classification, clustering, ranking, feature selection, prediction, etc.
• Issues such as selection of constituent models, fusion and diversity of models in an ensemble, etc.
• One-class classification and novelty detection
• One-class classifier ensembles,
• Diversity measures and ensemble pruning
• Classifier ensemble techniques for data stream classification
• Applications of an ensemble of computational intelligence methods in any field.
• Incremental online learning algorithms
• Detection and adaptation to the presence of the concept drift
• Imbalanced classification
• Discovery, detection and classification of complex patterns in massive or evolving data
• Semi-supervised approaches and active learning paradigms
• Scaling-up learning algorithms
• Near real-time analysis of massive data
• Integration and fusion of heterogeneous data structures and streams
• Distributed and parallel computing systems for big data analytics
• Problem of privacy in big and stream data
• Machine vision and object detection
• Applications to real-life problems from medicine, bioinformatics, multimedia, sensors, social networks and related domains

4. Interaction Studies and Semantic Communication (ISSC)
Track Chairs:
• Radosław Katarzyniak, Wrocław University of Technology, Poland
• Janusz Sobecki, Wrocław University of Technology, Poland
Human-Computer Interaction and semantic communication are complex processes that involve many stages of content processing. Both of them are described by competing and complementary models, each capturing multiple aspects of the social transfer of information or knowledge, describing the transfer from various theoretical perspectives and at various levels of representation and conceptualization. General topics for the track are defined to answer the following questions:
• how the content in different multimedia forms to be communicated is collected, stored and extracted from various classes of systems,
• what interaction techniques, models as well as semantic communication languages are used to carry the meaning between different interactive and intelligent artificial cognitive systems,
• how the meaning is developed and bound to the languages used by particular societies of artificial agents.
• how the quality of interaction and User Experience is evaluated and verified.
• The above general topics cover a broad list of detailed research sub-problems of theoretical and practical importance. Some of them are listed below:
• models, design and implementation of Natural User Interfaces,
• Augmented Reality and Virtual Reality systems models, design and applications
• User Experience and usability of interactive systems,
• models of artificial cognitive systems capable of semantic communication,
• ontologies, commitments and protocols in communication interaction,
• approaches to the extraction of linguistic summarizations of embodied knowledge bases,
• syntax, semantics and pragmatics of artificial semantic communication languages,
• application of machine learning and knowledge mining in communicative artificial cognitive systems,
• practical implementations (e.g. architectures with semantic communication capabilities).

5. Intelligent Techniques in Video and Document Analysis (InTViDo)
Track Chairs:
• Halina Kwasnicka, Wrocław University of Technology, Poland
• Urszula Markowska-Kaczmar, Wrocław University of Technology, Poland
The process of text, image, and video processing and mining, is a popular area of research and applications. The main scope of the InTViDo track is to provide an interdisciplinary forum for researchers and developers to present the latest advances in Artificial Intelligence in these wide fields. The track concentrates on machine learning techniques that enable to perform complex tasks over challenging data like image, video and text. The track aims to bring together specialists for exchanging ideas and fruitful discussions. We hope that the participants will benefit from the interdisciplinary nature of the conference. The emergence of potential joint research projects would be a great effect of the track.
• Researchers are welcome to submit papers covering but not limited to the following topics (algorithms and applications):
• Intelligent image/video interpretation
• Image/video indexing and retrieval
• Image/video annotation
• Intelligent video authentication
• Extracting textual characters in image/video
• Image/video processing restoration and enhancement
• Video summarization
• Text location in image/video
• Deep learning in video analysis
• Deep learning in image recognition
• Video analysis in road traffic, driving assistance, etc.
• Biometrics
• Medical image/video analysis and visualization
• Audio-visual analysis
• Sign language processing/understanding
• Filling the semantic gap in image analysis
• Foundations of multimedia information processing
• Document content analysis
• Document mining
• Sentiment analysis
• Document layout recognition
• Intelligent text recognition
• Natural language processing
• Deep learning in text documents analysis
• Foundations in natural language processing

We plan to publish the proceedings of ENIC 2016 by IEEE CPS.
The proceedings of the previous versions of ENIC were published by IEEE CPS and are available in IEEE Digital Library. The conference proceedings will be submitted for Web of Science indexing as well as EI indexing through INSPEC by IEEE.
Submission Instruction
Papers reporting original and unpublished research results pertaining to the above topics from both tracks are solicited. The papers will be reviewed by a minimum of two subject experts – Programme Committee members. Full paper manuscripts must be in English with a maximum length of 8 pages using the IEEE CPS two-column template. Papers should be submitted to the Conference Web site: with an additional selection of the right tracks. IEEE will retain the copyright for accepted papers, and the IEEE copyright form may be found at Papers will be accepted for the conference based on the reviewers comments on their originality, timeliness, significance, relevance, and clarity of presentation. If the paper is accepted, the paper will appear in the proceedings of the conference if one author presents the paper at the conference and at least one author register as a full conference participant.

Related Resources

IUI 2017   Intelligent User Interfaces
NIPS 2017   The Thirty-first Annual Conference on Neural Information Processing Systems
IEEE SSCI 2017   2017 IEEE Symposium Series on Computational Intelligence
ICONIP 2017   International Conference on Neural Information Processing
ICRAI 2017   2017 International Conference on Robotics and Artificial Intelligence
IPMU 2018   17th Information Processing and Management of Uncertainty in Knowledge-Based Systems Conference
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
ACML 2017   The 9th Asian Conference on Machine Learning
EJEMS - 2 2017   European Journal of Economics and Management Sciences
ICSC 2018   12th IEEE International Conference on Semantic Computing (ICSC 2018)