2,993 research outputs found
Dagstuhl News January - December 2008
"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic
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Towards an aspect weaving BPEL engine
This position paper proposes the use of dynamic aspects and
the visitor design pattern to obtain a highly configurable and
extensible BPEL engine. Using these two techniques, the
core of this infrastructural software can be customised to
meet new requirements and add features such as debugging,
execution monitoring, or changing to another Web Service
selection policy. Additionally, it can easily be extended to
cope with customer-specific BPEL extensions. We propose
the use of dynamic aspects not only on the engine itself
but also on the workflow in order to tackle the problems of
Web Service hot deployment and hot fixes to long running
processes. In this way, composing aWeb Service "on-the-fly"
means weaving its choreography interface into the workflow
Secured Client Portal
This project is aimed at developing an online search Portal for the Placement Department of the college. The system is an online application that can be accessed throughout the organization and outside as well with proper login provided. This system can be used as an Online Job Portal for the Placement Department of the college to manage the student information with regards to placement. Students logging should be able to upload their information in the form of a CV. Visitors/Company representatives logging in may also access/search any information put up by Students
The Future is Big Graphs! A Community View on Graph Processing Systems
Graphs are by nature unifying abstractions that can leverage
interconnectedness to represent, explore, predict, and explain real- and
digital-world phenomena. Although real users and consumers of graph instances
and graph workloads understand these abstractions, future problems will require
new abstractions and systems. What needs to happen in the next decade for big
graph processing to continue to succeed?Comment: 12 pages, 3 figures, collaboration between the large-scale systems
and data management communities, work started at the Dagstuhl Seminar 19491
on Big Graph Processing Systems, to be published in the Communications of the
AC
AAPOR Report on Big Data
In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.There is a great potential in Big Data but there are some fundamental challenges that have to be resolved before its full potential can be realized. In this report we give examples of different types of Big Data and their potential for survey research. We also describe the Big Data process and discuss its main challenges
Survey of Technologies for Web Application Development
Web-based application developers face a dizzying array of platforms,
languages, frameworks and technical artifacts to choose from. We survey,
classify, and compare technologies supporting Web application development. The
classification is based on (1) foundational technologies; (2)integration with
other information sources; and (3) dynamic content generation. We further
survey and classify software engineering techniques and tools that have been
adopted from traditional programming into Web programming. We conclude that,
although the infrastructure problems of the Web have largely been solved, the
cacophony of technologies for Web-based applications reflects the lack of a
solid model tailored for this domain.Comment: 43 page
A Framework for Discovery and Diagnosis of Behavioral Transitions in Event-streams
Date stream mining techniques can be used in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment. When the quality of some data mined models varies significantly from nearby models—as defined by quality metrics—then the user’s behavior is automatically flagged as a potentially significant behavioral change. Decision tree, sequence pattern and Hidden Markov modeling being used in this study. These three types of modeling can expose different aspect of user’s behavior. In case of decision tree modeling, the specific changes in user behavior can automatically characterized by differencing the data-mined decision-tree models. The sequence pattern modeling can shed light on how the user changes his sequence of actions and Hidden Markov modeling can identifies the learning transition points. This research describes how model-quality monitoring and these three types of modeling as a generic framework can aid recognition and diagnoses of behavioral changes in a case study of cognitive rehabilitation via emailing. The date stream mining techniques mentioned are used to monitor patient goals as part of a clinical plan to aid cognitive rehabilitation. In this context, real time data mining aids clinicians in tracking user behaviors as they attempt to achieve their goals. This generic framework can be widely applicable to other real-time data-intensive analysis problems. In order to illustrate this fact, the similar Hidden Markov modeling is being used for analyzing the transactional behavior of a telecommunication company for fraud detection. Fraud similarly can be considered as a potentially significant transaction behavioral change
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