10,379 research outputs found
Graph Summarization
The continuous and rapid growth of highly interconnected datasets, which are
both voluminous and complex, calls for the development of adequate processing
and analytical techniques. One method for condensing and simplifying such
datasets is graph summarization. It denotes a series of application-specific
algorithms designed to transform graphs into more compact representations while
preserving structural patterns, query answers, or specific property
distributions. As this problem is common to several areas studying graph
topologies, different approaches, such as clustering, compression, sampling, or
influence detection, have been proposed, primarily based on statistical and
optimization methods. The focus of our chapter is to pinpoint the main graph
summarization methods, but especially to focus on the most recent approaches
and novel research trends on this topic, not yet covered by previous surveys.Comment: To appear in the Encyclopedia of Big Data Technologie
XML content warehousing: Improving sociological studies of mailing lists and web data
In this paper, we present the guidelines for an XML-based approach for the
sociological study of Web data such as the analysis of mailing lists or
databases available online. The use of an XML warehouse is a flexible solution
for storing and processing this kind of data. We propose an implemented
solution and show possible applications with our case study of profiles of
experts involved in W3C standard-setting activity. We illustrate the
sociological use of semi-structured databases by presenting our XML Schema for
mailing-list warehousing. An XML Schema allows many adjunctions or crossings of
data sources, without modifying existing data sets, while allowing possible
structural evolution. We also show that the existence of hidden data implies
increased complexity for traditional SQL users. XML content warehousing allows
altogether exhaustive warehousing and recursive queries through contents, with
far less dependence on the initial storage. We finally present the possibility
of exporting the data stored in the warehouse to commonly-used advanced
software devoted to sociological analysis
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
A Taxonomy of Hyperlink Hiding Techniques
Hidden links are designed solely for search engines rather than visitors. To
get high search engine rankings, link hiding techniques are usually used for
the profitability of black industries, such as illicit game servers, false
medical services, illegal gambling, and less attractive high-profit industry,
etc. This paper investigates hyperlink hiding techniques on the Web, and gives
a detailed taxonomy. We believe the taxonomy can help develop appropriate
countermeasures. Study on 5,583,451 Chinese sites' home pages indicate that
link hidden techniques are very prevalent on the Web. We also tried to explore
the attitude of Google towards link hiding spam by analyzing the PageRank
values of relative links. The results show that more should be done to punish
the hidden link spam.Comment: 12 pages, 2 figure
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