Behavioral Pattern Detection using Compact and Fast Methods
This work proposes algorithms and methods for individual behavior detection within very large populations. One will consider domains where individual behavior presents some stable characteristics over time, and where the individual actions can be observed through events in a data stream. Event patterns will be characterized and used as a proxy to individual behavior and actions. As in many domains, behavior does not remain static but evolves over time; one will therefore consider the sliding window model, making the assumption that behavior is stable during the considered time window.
This work will cover the detection of the specific characteristics of the individual and what distinguishes his behavior from that of all other individuals. Algorithms must have minimal memory footprint and scalability to cope with huge number of individuals. Providing and keeping results up to date in near real time is also a goal, as information is only useful for limited periods in many situations. Fortunately, approximate answers are usually adequate for most problems.
Some fast and compact methods for diversity analysis will be introduced both for unlimited time and for the sliding window model. Innovative algorithms will be proposed to describe and characterize the individual event patterns. Those algorithms will then be used to create an individual event fingerprint. Using that fingerprint one will be able to identify the individual even when the identification information is not available. Distinct uses of the fuzzy fingerprint concept will be presented for individual identification that might also be extended to specific behavior identification, classification, profiling, etc., with examples in several domains such as internet traffic analysis, telecommunications fraud detection and text authorship analysis.
Date: 2011-Oct-28 Time: 15:00:00 Room: 020
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Workshop “Metabolism and mathematical models: Two for a tango” – 2nd Edition
Title: Workshop Metabolism and mathematical models: Two for a tango – 2nd Edition
Dates: October 25-26, 2022
Location: This workshop will be held in a virtual way
The topic of this workshop is metabolism in general, with a special focus, although not exclusive, on parasitology. Besides an exploration of the biological, biochemical and biomedical aspects, the workshop will also aim at presenting some of the mathematical modelling, algorithmic theory and software development that have become crucial to explore such aspects.
This workshop is being organised in the context of two projects, both with the Inria European Team Erable. One of the projects involves a partnership with the University of São Paulo (USP), in São Paulo, Brazil, more specifically the Institute of Mathematics and Statistics (IME) and the Institute of Biomedical Sciences – Inria Associated Team Capoeira – and the other involves the Inesc-ID/IST in Portugal, ETH in Zürich and EMBL in Heidelberg – H2020 Twinning Project Olissipo.
The workshop is open to all members of these two projects but also, importantly, to the community in general.
The program and more details are available here.