9,443 research outputs found
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
The Quest for Scalability and Accuracy in the Simulation of the Internet of Things: an Approach based on Multi-Level Simulation
This paper presents a methodology for simulating the Internet of Things (IoT)
using multi-level simulation models. With respect to conventional simulators,
this approach allows us to tune the level of detail of different parts of the
model without compromising the scalability of the simulation. As a use case, we
have developed a two-level simulator to study the deployment of smart services
over rural territories. The higher level is base on a coarse grained,
agent-based adaptive parallel and distributed simulator. When needed, this
simulator spawns OMNeT++ model instances to evaluate in more detail the issues
concerned with wireless communications in restricted areas of the simulated
world. The performance evaluation confirms the viability of multi-level
simulations for IoT environments.Comment: Proceedings of the IEEE/ACM International Symposium on Distributed
Simulation and Real Time Applications (DS-RT 2017
A Comparative Review on Computational Modeling Paradigms. A Study on Case-Based Modeling and Political Terrorism
We review the advances in Case-Based Computational Modeling on Political Analysis
issues. Starting in early â70s, the research on political terrorism has been challenged by the latest
advances of terrorism computational modeling research. Nowadays Political Analysis
community has a wider perspective over the terrorism research aims, methodology and
instruments. Widening up this perspective is not a matter of political analysis and research only, it
is as well a long-term effect of an interdisciplinary style which has been adopted within the area
by acknowledging the scientific advances and support of the Computational Modeling and
Simulation as a specific scientific research method. Computational Modeling includes several
research frameworks. The Case-Based Modeling is analysed and evaluated on a comparative basis
with Agent-Based Modeling in a study on political terrorism phenomena
Scenarios and research issues for a network of information
This paper describes ideas and items of work within the
framework of the EU-funded 4WARD project. We present
scenarios where the current host-centric approach to infor-
mation storage and retrieval is ill-suited for and explain
how a new networking paradigm emerges, by adopting the
information-centric network architecture approach, which
we call Network of Information (NetInf). NetInf capital-
izes on a proposed identifier/locator split and allows users
to create, distribute, and retrieve information using a com-
mon infrastructure without tying data to particular hosts.
NetInf introduces the concepts of information and data ob-
jects. Data objects correspond to the particular bits and
bytes of a digital object, such as text file, a specific encod-
ing of a song or a video. Information objects can be used
to identify other objects irrespective of their particular dig-
ital representation. After discussing the benefits of such an
indirection, we consider the impact of NetInf with respect
to naming and governance in the Future Internet. Finally,
we provide an outlook on the research scope of NetInf along
with items for future work
Multimodal Grounding for Language Processing
This survey discusses how recent developments in multimodal processing
facilitate conceptual grounding of language. We categorize the information flow
in multimodal processing with respect to cognitive models of human information
processing and analyze different methods for combining multimodal
representations. Based on this methodological inventory, we discuss the benefit
of multimodal grounding for a variety of language processing tasks and the
challenges that arise. We particularly focus on multimodal grounding of verbs
which play a crucial role for the compositional power of language.Comment: The paper has been published in the Proceedings of the 27 Conference
of Computational Linguistics. Please refer to this version for citations:
https://www.aclweb.org/anthology/papers/C/C18/C18-1197
Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come
In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers â the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things â in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future
Identifying communicator roles in Twitter
Twitter has redefined the way social activities can be coordinated; used for mobilizing people during natural disasters, studying health epidemics, and recently, as a communication platform during social and political change. As a large scale system, the volume of data transmitted per day presents Twitter users with a problem: how can valuable content be distilled from the back chatter, how can the providers of valuable information be promoted, and ultimately how can influential individuals be identified?To tackle this, we have developed a model based upon the Twitter message exchange which enables us to analyze conversations around specific topics and identify key players in a conversation. A working implementation of the model helps categorize Twitter users by specific roles based on their dynamic communication behavior rather than an analysis of their static friendship network. This provides a method of identifying users who are potentially producers or distributers of valuable knowledge
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