1,200 research outputs found
A query description model based on basic semantic unit composite Petri-Net for soccer video
Digital video networks are making available increasing amounts of sports video data. The volume of material on offer means that sports fans often rely on prepared summaries of game highlights to follow the progress of their favourite teams. A significant application area for automated video analysis technology is the generation of personalized highlights of sports events. One of the most popular sports around world is soccer. A soccer game is composed of a range of significant events, such as goal scoring, fouls, and substitutions. Automatically detecting these events in a soccer video can enable users to interactively design their own highlights programmes. From an analysis of broadcast soccer video, we propose a query description model based on Basic Semantic Unit Composite Petri-Nets (BSUCPN) to automatically detect significant events within soccer video. Firstly we define a Basic Semantic Unit (BSU) set for soccer videos based on identifiable feature elements within a soccer video, Secondly we design Composite Petri-Net (CPN) models for semantic queries and use these to describe BSUCPNs for semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic event queries based on BSUCPNs to search interactively within soccer videos. Experimental results
based on recorded soccer broadcasts are used to illustrate the potential of this approach
Evaluating openEHR for storing computable representations of electronic health record phenotyping algorithms
Electronic Health Records (EHR) are data generated during routine clinical
care. EHR offer researchers unprecedented phenotypic breadth and depth and have
the potential to accelerate the pace of precision medicine at scale. A main EHR
use-case is creating phenotyping algorithms to define disease status, onset and
severity. Currently, no common machine-readable standard exists for defining
phenotyping algorithms which often are stored in human-readable formats. As a
result, the translation of algorithms to implementation code is challenging and
sharing across the scientific community is problematic. In this paper, we
evaluate openEHR, a formal EHR data specification, for computable
representations of EHR phenotyping algorithms.Comment: 30th IEEE International Symposium on Computer-Based Medical Systems -
IEEE CBMS 201
Asymptotically Truthful Equilibrium Selection in Large Congestion Games
Studying games in the complete information model makes them analytically
tractable. However, large player interactions are more realistically
modeled as games of incomplete information, where players may know little to
nothing about the types of other players. Unfortunately, games in incomplete
information settings lose many of the nice properties of complete information
games: the quality of equilibria can become worse, the equilibria lose their
ex-post properties, and coordinating on an equilibrium becomes even more
difficult. Because of these problems, we would like to study games of
incomplete information, but still implement equilibria of the complete
information game induced by the (unknown) realized player types.
This problem was recently studied by Kearns et al. and solved in large games
by means of introducing a weak mediator: their mediator took as input reported
types of players, and output suggested actions which formed a correlated
equilibrium of the underlying game. Players had the option to play
independently of the mediator, or ignore its suggestions, but crucially, if
they decided to opt-in to the mediator, they did not have the power to lie
about their type. In this paper, we rectify this deficiency in the setting of
large congestion games. We give, in a sense, the weakest possible mediator: it
cannot enforce participation, verify types, or enforce its suggestions.
Moreover, our mediator implements a Nash equilibrium of the complete
information game. We show that it is an (asymptotic) ex-post equilibrium of the
incomplete information game for all players to use the mediator honestly, and
that when they do so, they end up playing an approximate Nash equilibrium of
the induced complete information game. In particular, truthful use of the
mediator is a Bayes-Nash equilibrium in any Bayesian game for any prior.Comment: The conference version of this paper appeared in EC 2014. This
manuscript has been merged and subsumed by the preprint "Robust Mediators in
Large Games": http://arxiv.org/abs/1512.0269
Representing, storing and mining moving objects data
Data about moving objects have been collected in huge amounts due to the proliferation of mobile devices, which
capture the position of objects over time. Studies about moving objects have been developed as a specific research area of
Geographic Information Systems. Those systems are designed to process traditional, static or slowly changing, geospatial
data. However, moving objects have inherent a dynamism that requires different approaches to data storage and analysis.
This paper presents a review of the key concepts associated to moving objects and their characteristics, as well as the
approaches proposed to store data about moving objects. For the analysis of moving objects, an overview of the existing data
mining techniques and some future guidelines are also presented
Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms
Electronic Health Records are electronic data generated during or as a
byproduct of routine patient care. Structured, semi-structured and unstructured
EHR offer researchers unprecedented phenotypic breadth and depth and have the
potential to accelerate the development of precision medicine approaches at
scale. A main EHR use-case is defining phenotyping algorithms that identify
disease status, onset and severity. Phenotyping algorithms utilize diagnoses,
prescriptions, laboratory tests, symptoms and other elements in order to
identify patients with or without a specific trait. No common standardized,
structured, computable format exists for storing phenotyping algorithms. The
majority of algorithms are stored as human-readable descriptive text documents
making their translation to code challenging due to their inherent complexity
and hinders their sharing and re-use across the community. In this paper, we
evaluate the two key Semantic Web Technologies, the Web Ontology Language and
the Resource Description Framework, for enabling computable representations of
EHR-driven phenotyping algorithms.Comment: Accepted American Medical Informatics Association Annual Symposium
201
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