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International Workshop on New Frontiers in Mining Complex Patterns

Quando 19/09/2016
dalle 09:00 alle 19:00
Dove Riva del Garda-Italy
PartecipantiAnnalisa 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

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Pubblicato il: 20/05/2016