5,165 research outputs found
Living analytics methods for the social web
[no abstract
Semantic Stability in Social Tagging Streams
One potential disadvantage of social tagging systems is that due to the lack
of a centralized vocabulary, a crowd of users may never manage to reach a
consensus on the description of resources (e.g., books, users or songs) on the
Web. Yet, previous research has provided interesting evidence that the tag
distributions of resources may become semantically stable over time as more and
more users tag them. At the same time, previous work has raised an array of new
questions such as: (i) How can we assess the semantic stability of social
tagging systems in a robust and methodical way? (ii) Does semantic
stabilization of tags vary across different social tagging systems and
ultimately, (iii) what are the factors that can explain semantic stabilization
in such systems? In this work we tackle these questions by (i) presenting a
novel and robust method which overcomes a number of limitations in existing
methods, (ii) empirically investigating semantic stabilization processes in a
wide range of social tagging systems with distinct domains and properties and
(iii) detecting potential causes for semantic stabilization, specifically
imitation behavior, shared background knowledge and intrinsic properties of
natural language. Our results show that tagging streams which are generated by
a combination of imitation dynamics and shared background knowledge exhibit
faster and higher semantic stability than tagging streams which are generated
via imitation dynamics or natural language streams alone
Intelligent Management and Efficient Operation of Big Data
This chapter details how Big Data can be used and implemented in networking
and computing infrastructures. Specifically, it addresses three main aspects:
the timely extraction of relevant knowledge from heterogeneous, and very often
unstructured large data sources, the enhancement on the performance of
processing and networking (cloud) infrastructures that are the most important
foundational pillars of Big Data applications or services, and novel ways to
efficiently manage network infrastructures with high-level composed policies
for supporting the transmission of large amounts of data with distinct
requisites (video vs. non-video). A case study involving an intelligent
management solution to route data traffic with diverse requirements in a wide
area Internet Exchange Point is presented, discussed in the context of Big
Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big
Data and Web Intelligence, IGI Global, 201
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