Social Semantic Web Mining
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Numar articol:205577761
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Anuntul a expirat la:12.01.2023, 11:01
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Specificatii
The past ten years have seen a rapid growth in the numbers of
people signing up to use Web-based social networks (hundreds of
millions of new members are now joining the main services each
year) with a large amount of content being shared on these networks
(tens of billions of content items are shared each month). With
this growth in usage and data being generated, there are many
opportunities to discover the knowledge that is often inherent but
somewhat hidden in these networks. Web mining techniques are being
used to derive this hidden knowledge. In addition, the Semantic
Web, including the Linked Data initiative to connect previously
disconnected datasets, is making it possible to connect data from
across various social spaces through common representations and
agreed upon terms for people, content items, etc. In this book, we
detail some current research being carried out to semantically
represent the implicit and explicit structures on the Social Web,
along with the techniques being used to elicit relevant knowledge
from these structures, and we present the mechanisms that can be
used to intelligently mesh these semantic representations with
intelligent knowledge discovery processes. We begin this book with
an overview of the origins of the Web, and then show how web
intelligence can be derived from a combination of web and Social
Web mining. We give an overview of the Social and Semantic Webs,
followed by a description of the combined Social Semantic Web
(along with some of the possibilities it affords), and the various
semantic representation formats for the data created in social
networks and on social media sites. Provenance and provenance
mining is an important aspect here, especially when data is
combined from multiple services. We will expand on the subject of
provenance and especially its importance in relation to social
data. We will describe extensions to social semantic vocabularies
specifically designed for community mining purposes (SIOCM). In the
last three chapters, we describe how the combination of web
intelligence and social semantic data can be used to derive
knowledge from the Social Web, starting at the community level
(macro), and then moving through group mining (meso) to user
profile mining (micro). Table of Contents: Acknowledgments / Grant
Aid / Introduction and the Web / Web Mining / The Social Web / The
Semantic Web / The Social Semantic Web / Social Semantic Web Mining
/ Social Semantic Web Mining of Communities / Social Semantic Web
Mining of Groups / Social Semantic Web Mining of Users /
Conclusions / Bibliography / Authors' Biographies
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