The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
The peer sampling service: experimental evaluation of unstructured gossip-based implementations
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Efficient network aware search in collaborative tagging sites
Proceedings of the VLDB Endowment
Social ranking: uncovering relevant content using tag-based recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Tag data and personalized information retrieval
Proceedings of the 2008 ACM workshop on Search in social media
T-Man: gossip-based overlay topology management
ESOA'05 Proceedings of the Third international conference on Engineering Self-Organising Systems
Challenges in Personalizing and Decentralizing the Web: An Overview of GOSSPLE
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Folksonomy-based reasoning for content dissemination in mobile settings
Proceedings of the 5th ACM workshop on Challenged networks
Query expansion in folksonomies
SAMT'10 Proceedings of the 5th international conference on Semantic and digital media technologies
Improving search via personalized query expansion using social media
Information Retrieval
Web search personalization using social data
TPDL'12 Proceedings of the Second international conference on Theory and Practice of Digital Libraries
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Social networking and tagging have taken off at an unexpected scale and speed, opening huge opportunities to enhance the user search experience. We present Gossple, a new, user-centric, approach to improve the exploration of the Internet. Underlying Gossple lies the intuition that while social networks provides news from your old buddies, you can learn a lot more from people you don't know, but with whom you share many (tagging) interests. More specifically, considering a collaborative tagging system with active taggers annotating content, Gossple expands the search query, of any user u, with tags that are considered "close" enough with respect to users that are "close" to u. Gossple users create their own network of social acquaintances in a gossip-based manner, by dynamically computing the estimation of a distance between taggers, based on cosine similarity between tags and items. These connections are used to feed a TagMap: our central abstraction that captures the personalised relationships between tags. The TagMap is then used by Gossple to meaningfully expand queries leveraging the personalised network. This is achieved through the TagRank algorithm, an adaptation of the celebrated pagerank algorithm, which automatically determines which tags best expand a list of tags in a given query. Gossple has no central authority: every user stores its own items and its tagging behaviour is stored only by its neighbours. The resulting networks are live, dynamic and do not require any underlying structure. We report on our evaluation of Gossple with CiteUlike traces, involving 33,834 users. In short, we show that, with little information stored at every peer, Gossple enables to retrieve items that cannot be retrieved with state of the art search systems (completeness).