37,194 research outputs found
Entity Identification Problem in Big and Open Data
Big and Open Data provide great opportunities to businesses to enhance their competitive advantages if
utilized properly. However, during past few years’ research in Big and Open Data process, we have
encountered big challenge in entity identification reconciliation, when trying to establish accurate
relationships between entities from different data sources. In this paper, we present our innovative Intelligent
Reconciliation Platform and Virtual Graphs solution that addresses this issue. With this solution, we are able
to efficiently extract Big and Open Data from heterogeneous source, and integrate them into a common
analysable format. Further enhanced with the Virtual Graphs technology, entity identification reconciliation
is processed dynamically to produce more accurate result at system runtime. Moreover, we believe that our
technology can be applied to a wide diversity of entity identification problems in several domains, e.g., e-
Health, cultural heritage, and company identities in financial world.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-
Complex Actions for Event Processing
Automatic reactions triggered by complex events have been
deployed with great success in particular domains, among
others, in algorithmic trading, the automatic reaction to realtime
analysis of marked data. However, to date, reactions
in complex event processing systems are often still limited
to mere modifications of internal databases or are realized
by means similar to remote procedure calls.
In this paper, we argue that expressive complex actions
with support for composite work
ows and integration of
so called external actions are desirable for a wide range
of real-world applications among other emergency management.
This article investigates the particularities of external
actions needed in emergency management, which are initiated
inside the event processing system but which are actually
executed by external actuators, and discuss the implications
of these particularities on composite actions. Based
on these observations, we propose versatile complex actions
with temporal dependencies and a seamless integration of
complex events and external actions. This article also investigates
how the proposed integrated approach towards
complex events and complex actions can be evaluated based
on simple reactive rules. Finally, it is shown how complex actions
can be deployed for a complex event processing system
devoted to emergency management
Dura
The reactive event processing language, that is developed in the context of this project, has been called DEAL in previous documents. When we chose this name for our language it has not been used by other authors working in the same research area (complex event processing). However, in the meantime it appears in publications of other authors and because we have not used the name in publications yet we cannot claim that we were the first to use it. In order to avoid ambiguities and name conflicts in future publications we decided to rename our language to Dura which stands for “Declarative uniform reactive event processing language”. Therefore the title of this deliverable has been updated to “Dura – Concepts and Examples”
When resources collide: Towards a theory of coincidence in information spaces
This paper is an attempt to lay out foundations for a general theory of coincidence in information spaces such as the World Wide Web, expanding on existing work on bursty structures in document streams and information cascades. We elaborate on the hypothesis that every resource that is published in an information space, enters a temporary interaction with another resource once a unique explicit or implicit reference between the two is found. This thought is motivated by Erwin Shroedingers notion of entanglement between quantum systems. We present a generic information cascade model that exploits only the temporal order of information sharing activities, combined with inherent properties of the shared information resources. The approach was applied to data from the world's largest online citizen science platform Zooniverse and we report about findings of this case study
Forensic Analysis of the ChatSecure Instant Messaging Application on Android Smartphones
We present the forensic analysis of the artifacts generated on Android
smartphones by ChatSecure, a secure Instant Messaging application that provides
strong encryption for transmitted and locally-stored data to ensure the privacy
of its users.
We show that ChatSecure stores local copies of both exchanged messages and
files into two distinct, AES-256 encrypted databases, and we devise a technique
able to decrypt them when the secret passphrase, chosen by the user as the
initial step of the encryption process, is known.
Furthermore, we show how this passphrase can be identified and extracted from
the volatile memory of the device, where it persists for the entire execution
of ChatSecure after having been entered by the user, thus allowing one to carry
out decryption even if the passphrase is not revealed by the user.
Finally, we discuss how to analyze and correlate the data stored in the
databases used by ChatSecure to identify the IM accounts used by the user and
his/her buddies to communicate, as well as to reconstruct the chronology and
contents of the messages and files that have been exchanged among them.
For our study we devise and use an experimental methodology, based on the use
of emulated devices, that provides a very high degree of reproducibility of the
results, and we validate the results it yields against those obtained from real
smartphones
ATLAS: A flexible and extensible architecture for linguistic annotation
We describe a formal model for annotating linguistic artifacts, from which we
derive an application programming interface (API) to a suite of tools for
manipulating these annotations. The abstract logical model provides for a range
of storage formats and promotes the reuse of tools that interact through this
API. We focus first on ``Annotation Graphs,'' a graph model for annotations on
linear signals (such as text and speech) indexed by intervals, for which
efficient database storage and querying techniques are applicable. We note how
a wide range of existing annotated corpora can be mapped to this annotation
graph model. This model is then generalized to encompass a wider variety of
linguistic ``signals,'' including both naturally occuring phenomena (as
recorded in images, video, multi-modal interactions, etc.), as well as the
derived resources that are increasingly important to the engineering of natural
language processing systems (such as word lists, dictionaries, aligned
bilingual corpora, etc.). We conclude with a review of the current efforts
towards implementing key pieces of this architecture.Comment: 8 pages, 9 figure
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