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6 Conclusion and Future Work
In this paper, we proposed a new gossip-based search and recommendation ap-
proach with new measures and techniques. We first showed that usefulness, by
combining relevance and diversity, is very effective in increasing recall results
and can be used as a clustering score. Then, we designed a new clustering algo-
rithm based on usefulness that combines relevance and diversity. We validated
our proposal with an experimental evaluation using several datasets and show
major gains with recall results more than two times better.
In future work we intend to exploit other recommendation scenarios such as
multisite recommendation.
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