Social tagging networks have become highly popular for publishing and
searching contents. Users in such networks can review, rate and comment
on contents, or annotate them with keywords (social tags) to give
short but exact text representations of even non-textual contents.
Moreover, there is an inherent support for interactions and relationships
among users and, thus, naturally form groups of friends or of common
interests.
This dissertation addresses in this area three research topics, namely:
i) A comprehensive framework for search in social tagging networks and
efficient top-k result retrieval. (ii) A new approach of solving the APSD Problem
for dynamically update friendship relations in large user networks. (iii)
Countering cheating in P2P authority computations over social networks.