International Workshop on New Frontiers in Mining Complex Patterns
- https://www.uniba.it/it/ricerca/dipartimenti/informatica/notizie-eventi/eventi/international-workshop-on-new-frontiers-in-mining-complex-patterns
- International Workshop on New Frontiers in Mining Complex Patterns
- 2016-09-19T09:00:00+02:00
- 2016-09-19T19:00:00+02:00
- Quando il 19/09/2016 dalle 09:00 alle 19:00 (Europe/Berlin / UTC200)
- Dove Riva del Garda-Italy
- Partecipanti Annalisa Appice, Michelangelo Ceci, Corrado Loglisci
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5th International Workshop on New Frontiers in Mining Complex Patterns (in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), to be held in Riva del Garda from September 19th to 23rd, 2016. )
Modern automatic systems are able to collect huge volumes of data, often with a complex structure (e.g. multi-table data, XML data, web data, time series and sequences, graphs and trees). This fact poses new challenges for current information systems with respect to storing, managing and mining these big sets of complex data.
The purpose of this workshop is to bring together researchers and practitioners of data mining who are interested in the advances and latest developments in the area of extracting patterns from big and complex data sources like blogs, event or log data, biological data, spatio-temporal data, social networks, mobility data, sensor data and streams, and so on. The workshop aims at integrating recent results from existing fields such as data mining, statistics, machine learning and relational databases to discuss and introduce new algorithmic foundations and representation formalisms in pattern discovery. We are interested in advanced techniques which preserve the informative richness of data and allow us to efficiently and efficaciously identify complex information units present in such data.
A non-exclusive list of topics for the complex pattern mining research is reported in the following:
Foundations on pattern mining, pattern usage, and pattern understanding
Mining stream, time-series and sequence data
Mining networks and graphs
Mining biological data
Mining dynamic and evolving data
Mining environmental and scientific data
Mining heterogeneous and ubiquitous data
Mining multimedia data
Mining multi-relational data
Mining semi-structured and unstructured data
Mining spatio-temporal data
Mining Big Data
Social Media Analytics
Ontology and metadata
Privacy preserving mining
Semantic Web and Knowledge Databases