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Aristides Gionis
Researcher at Royal Institute of Technology
Publications - 316
Citations - 21244
Aristides Gionis is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Approximation algorithm & Graph (abstract data type). The author has an hindex of 58, co-authored 292 publications receiving 19300 citations. Previous affiliations of Aristides Gionis include Yahoo! & Aalto University.
Papers
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Proceedings ArticleDOI
Improving recommendation for long-tail queries via templates
TL;DR: This work proposes a method to extend the reach of query assistance techniques (and in particular query recommendation) to long-tail queries by reasoning about rules between query templates rather than individual query transitions, as currently done in query-flow graph models.
Journal ArticleDOI
Design trade-offs for search engine caching
Ricardo Baeza-Yates,Aristides Gionis,Flavio Junqueira,Vanessa Murdock,Vassilis Plachouras,Fabrizio Silvestri +5 more
TL;DR: Using a query log spanning a whole year, it is demonstrated that caching posting lists can achieve higher hit rates than caching query answers and a new algorithm is proposed for static caching of posting lists, which outperforms previous methods.
Proceedings ArticleDOI
Customized tour recommendations in urban areas
TL;DR: This paper focuses on the problem of recommending customized tours in urban settings, and introduces two instances of the TourRec problem, study their complexity, and propose efficient algorithmic solutions.
Proceedings ArticleDOI
k-Anonymization Revisited
TL;DR: New notions of k-type anonymizations are introduced, which allow generalized tables that may offer higher utility than k-anonymized tables, while still preserving the required privacy constraints.
Journal ArticleDOI
Efficient algorithms for large-scale local triangle counting
TL;DR: The measures the authors compute can help detect the presence of spamming activity in large-scale Web graphs, as well as to provide useful features for content quality assessment in social networks.