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DyNAK 2010 : Workshop on Dynamic Networks and Knowledge Discovery


When Sep 24, 2010 - Sep 24, 2010
Where Barcalona
Submission Deadline Jun 28, 2010
Notification Due Jul 12, 2010
Final Version Due Jul 21, 2010
Categories    machine learning   knowledge discovery   social networks   data mining

Call For Papers

Modeling and analyzing networks is a major emerging topic in different research areas, such as computational biology, social science, document retrieval, etc. By connecting objects, it is possible to obtain an intuitive and global view of the relationships between components of a complex system.

Nowadays, the scientific communities have access to huge volumes of network-structured data, such as social networks, gene/proteins/metabolic networks, sensor networks, peer-to-peer networks. Most often, these data are not only static, but they are collected at different time points. This dynamic view of the system allows the time component to play a key role in the comprehension of the evolutionary behavior of the network (evolution of the network structure and/or of flows within the system). Time can help to determine the real causal relationships within, for instance, gene activations, link creation, information flow.

Handling such data is a major challenge for current research in machine learning and data mining, and it has led to the development of recent innovative techniques that consider complex/multi-level networks, time-evolving graphs, heterogeneous information (nodes and links), and requires scalable algorithms that are able to manage huge and complex networks.

DyNaK workshop is motivated by the interest of providing a meeting point for scientists with different backgrounds that are interested in the study of large complex networks and the dynamic aspects of such networks. It aims at attracting contributions from both aspects of networks analysis: large real network analysis and modelling, and knowledge discovery within those networks. Even though each type of real complex networks has some peculiarities related to its specific domain, many aspects of the modeling and mining techniques for such networks are shareable. For instance, gene networks and social networks share a common architecture (scale-free), and involve similar data mining and machine learning methods: module/community extraction, hub single-out, information-flow analysis, missing link detection and link prediction.

Special session on Sentiment Analysis and Opinion Mining
Every day, millions of people write their opinions about any issue in social media, such as social news sites, review sites, and blogs. The distillation of knowledge from this huge amount of unstructured information is a challenging task. Sentiment Analysis and Opinion Mining are two areas related to Natural Language Processing and Text Mining that deal with the identification of opinions and attitudes in natural language texts. In the Opinion Mining session of DyNaK we are interested in research results from academics and practitioners in the task of extracting knowledge from user generated contents, and how time affects to this analysis.

Topics of interest
Contributions to the DyNaK workshop should be focused on this (non exhaustive) list of topics:

Network inference from raw data
Graphical models
Graph mining algorithms
Graph kernel algorithms
Relational learning algorithms
Matrix/Tensor methods
Information retrieval algorithms
Bayesian methods
Evolutionary clustering
Mining and learning from heterogenous domains
Bisociative information discovery
Pattern mining and clustering with constraints
Community detection/Module extraction
Analogies between social and biological networks
Opinion Extraction and Classification
Blogs Analysis and Social Search
Temporal Sentiment Analysis
Irony and Plagiarism detection in Opinion Mining
Recommender Systems
System biology: regulatory gene networks, protein-protein interaction, miRNA networks, metabolic networks
Social networks: folksonomies, digital libraries, information networks, social media, collaborative networks
Sensor networks, peer-to-peer networks, Web, agent networks, body sensor networks

Related Resources

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ICDM 2018   IEEE International Conference on Data Mining
ECML-PKDD 2018   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
CIKM 2018   International Conference on Information and Knowledge Management
PAKDD 2018   The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining
ICANN 2018   27th International Conference on Artificial Neural Networks
ACML 2018   The 10th Asian Conference on Machine Learning
KDIR 2018   10th International Conference on Knowledge Discovery and Information Retrieval
Ei DMKD 2018   2018 International Conference on Data Mining and Knowledge Discovery(DMKD 2018)
IEEE DySPAN 2018   IEEE International Symposium on Dynamic Spectrum Access Networks