MHDW 2013 - 2nd Mining Humanistic Data Workshop

The abundance of available data that is retrieved from or is related to the areas of Humanities and the human condition challenges the research community in processing and analyzing it. The aim is two-fold: on the one hand, to extract knowledge that will help understand human behavior, creativity, way of thinking, reasoning, learning, decision making, socializing and even biological processes; on the other hand, to exploit the extracted knowledge by incorporating it into intelligent systems that will support humans in their everyday activities.
The nature of humanistic data can be multimodal, semantically heterogeneous, dynamic, time and space-dependent, and highly complicated. Translating humanistic information, e.g. behavior, state of mind, artistic creation, linguistic utterance, learning and genomic information into numerical or categorical low-level data is a significant challenge on its own. New techniques, appropriate to deal with this type of data, need to be proposed and existing ones adapted to its special characteristics.
The workshop aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing data matching, fusion and mining and knowledge discovery and management techniques (like decision rules, decision trees, association rules, ontologies and alignments, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques) to data derived from all areas of Humanistic Sciences, e.g. linguistic, historical, behavioral, psychological, artistic, musical, educational, social etc., Ubiquitous Computing and Bioinformatics.
Ubiquitous Computing applications (aka Pervasive Computing, Mobile Computing, Ambient Intelligence, etc.) collect large volumes of usually heterogeneous data in order to effect adaptation, learning and in general context awareness. Data matching, fusion and mining techniques are necessary to ensure human centred application functionality.
An important aspect of humanistics centers around managing, processing and computationally analyzing Biological and Biomedical data. Hence, one of the aims of this workshop will be to also attract researchers that are interested in designing, developing and applying efficient data and text mining techniques for discovering the underlying knowledge existing in Biomedical data, such as sequences, gene expressions and pathways.
Workshop Topics
The workshop topics include but are not limited to:
Humanistic Data Collection and Interpretation
Data pre-processing
Feature Selection
Supervised learning of humanistic knowledge
Clustering
Fuzzy modeling
Heterogeneous data fusion
Knowledge Representation and Reasoning
Linguistic Data Mining
Historical Research
Educational Data Mining
Music Information Retrieval
Data-driven Profiling/ Personalization
User Modeling
Behavior Prediction
Recommender Systems
Web Sentiment Analysis
Social Data Mining
Visualization techniques
Integration of data mining results into real-world applications with humanistic context
Ontologies, ontology matching and alignment
Mining Humanistic Data in the Cloud
Game Data Mining
Virtual-World Data Mining
Speech and Audio Data Processing
Data Mining Techniques for Knowledge Discovery
Biomedical Data Mining
Protein structure prediction
Submission
All papers should be submitted through easychair. Papers should be submitted either in a doc or in a pdf form and they will be peer reviewed by at least 2 academic referees. Papers should not exceed 10 pages. Contributing authors must follow the Springer Lecture Notes in Computer Science (LNCS) instructions for authors.
Publication
Accepted papers will be presented orally in the conference for 20 minutes and they will be published in the Proceedings of the main event.