5th Mining Humanistic Data Workshop (MHDW 2016)
When : 2016-09-16
Where : Greece
Submission Deadline : 2016-04-27
Categories : Artificial Intelligence , Data Mining
5th Mining Humanistic Data Workshop (MHDW 2016)
September 16-18, 2016
Greece
Call For Papers
The 5th Mining Humanistic Data Workshop aims to bring together interdisciplinary approaches that focus on the application of innovative, as well as existing, data matching, fusion and mining, knowledge discovery and management, techniques, like for instance decision rules and trees, association rules, ontologies and alignments, clustering, filtering, supervised or unsupervised learning, classifier systems, neural networks, support vector machines, pre- or post-processing, feature selection, visualization techniques, et al.. To illustrate human-centered application functionalities, data management approached derived from all fields of humanistic sciences, like linguistic, historical, behavioral, psychological, artistic, musical, educational, social or other types of data, will be also welcomed in the framework of this community. Research efforts that typically collect large volumes of usually heterogeneous data, like ubiquitous computing applications (aka pervasive or mobile computing, ambient intelligence, etc.) or big data mining methodologies are also encouraged in the sense of content adaptation, learning and overall context awareness. Last, but not least an important aspect of related human-centered research efforts in informatics deals also with the managing, processing and computationally analyzing of biological and biomedical data within the broader scope of bioinformatics. Hence, one of the aims of this workshop will be to also attract researchers interested in designing, developing and applying efficient data mining techniques for discovering the underlying knowledge inherent in such data, such as sequences, gene expressions and pathways.
Topics
- Humanistic data collection and interpretation- Data pre-processing
- Feature selection methodologies
- Supervised or unsupervised learning of humanistic knowledge
- Clustering/Classification techniques
- Fuzzy modeling
- Heterogeneous data fusion
- Knowledge representation and reasoning
- Linguistic data mining
- Educational data mining
- Music information retrieval
- Data-driven profiling/ personalization
- User modeling
- Behavior prediction
- Recommender systems
- Web sentiment analysis
- Social data mining
- Data 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
- Bioinformatics
- Content creation, annotation and modeling for semantic and social web
- Computational intelligence for media adaptation and personalization
- Semantics-driven indexing and retrieval of multimedia contents
- Semantic context modeling and extraction
- Context-aware applications
- Social web economics and business
- Privacy/security issues in social and personalized applications
- Privacy preserving data mining and social networks
- Social data analytic