• Corpus ID: 6132095

Privacy aware social information retrieval and spam filtering using folksonomies

@inproceedings{Krause2015PrivacyAS,
  title={Privacy aware social information retrieval and spam filtering using folksonomies},
  author={Beate Krause},
  year={2015}
}
Social interactions as introduced by Web 2.0 applications during the last decade have changed the way the Internet is used. Today, it is part of our daily lives to maintain contacts through social networks, to comment on the latest developments in microblogging services or to save and share information snippets such as photos or bookmarks online. Social bookmarking systems are part of this development. Users can share links to interesting web pages by publishing bookmarks and providing… 

References

SHOWING 1-10 OF 164 REFERENCES
Logsonomy - social information retrieval with logdata
TLDR
It is concluded that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.
Post-Level Spam Detection for Social Bookmarking Web Sites
TLDR
This work proposes a method based on a text mining approach to discover the relations between Web pages and there tag posts that are then used to compute the similarity between a Web page and its tag post to decide if it is a spam post.
A Comparison of Social Bookmarking with Traditional Search
TLDR
This study compares search in social bookmarking systems with traditionalWeb search, and shows that a graph-based ranking approach on folksonomies yields results that are closer to the rankings of the commercial search engines than vector space retrieval, and that the correlation is high in particular for the domains that are well covered by thesocial bookmarking system.
Privacy-aware spam detection in social bookmarking systems
TLDR
A data privacy aware feature engineering approach which consists of the design of features for spam classification which are evaluated according to both, performance and privacy conditions and experiments show that both conditions must not exclude each other.
Improving search via personalized query expansion using social media
TLDR
A novel query expansion framework based on individual user profiles mined from the annotations and resources the user has marked that significantly benefits personalized web search by leveraging users’ social media data.
Understanding and leveraging the social web for information retrieval
TLDR
This thesis investigates the notion of expertise or “trustworthiness” of users in folksonomies and presents the proposed algorithm, SPEAR, for ranking users by their expertise and presents three use cases that demonstrate how their results can be leveraged for enhancing and improving Web information retrieval.
A Novel Framework for Spammer Detection in Social Bookmarking Systems
TLDR
A novel framework for spam detection task in social bookmarking systems is introduced and a set of new features are proposed to improve the accuracy of spammer detection.
A social inverted index for social-tagging-based information retrieval
TLDR
A social inverted index is proposed – a novel inverted index extended for social-tagging-based IR – that maintains a separate user sublist for each resource in a resource-posting list to contain each user’s various features as weights.
Folksonomy-based ad hoc community detection in online social networks
TLDR
It is hypothesize that the ad hoc communities of users sharing similar interests embedded in a folksonomy-based social network can be identified by overlapping tag clusters in the tag concept hierarchy.
Friend Recommendation in a Social Bookmarking System: Design and Architecture Guidelines
TLDR
This paper presents an analysis of the state-of-the-art on user recommendation in social environments and of the structure of a social bookmarking system, in order to derive design guidelines and an architecture of a friend recommender system in thesocial bookmarking domain.
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