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Searching for authors named "Panos Kalnis" – sorted by Relevance.

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  • Multi-query Optimization for On-Line Analytical Processing  
  • by Panos Kalnis, Dimitris Papadias — 1998 — in Wireless Communications: Signal Processing Perspectives, eds. H.V. Poor and G.W. Wornell, Upper Saddle River, NJ
  • …Multi-Dimensional Expressions (MDX) provide an interface for asking several related OLAP queries simultaneously. An interesting problem is how to optimize the execution of an MDX query, given that most data warehouses maintain a set of redundant materialized views to accelerate OLAP operations. A …
  • Cited by 1 (0 self) – Add To MetaCart
  • Proxy-Server Architectures for OLAP  
  • by Panos Kalnis, Dimitris Papadias — 2001 — In SIGMOD
  • …Data warehouses have been successfully employed for assisting decision making by offering a global view of the enterprise data and providing mechanisms for On-Line Analytical processing. Traditionally, data warehouses are utilized within the limits of an enterprise or organization. The growth of Int…
  • Cited by 7 (2 self) – Add To MetaCart
  • On the Anonymization of Sparse High-Dimensional Data  
  • by Gabriel Ghinita, Panos Kalnis
  • …Abstract — Existing research on privacy-preserving data publishing focuses on relational data: in this context, the objective is to enforce privacy-preserving paradigms, such as kanonymity and ℓ-diversity, while minimizing the information loss incurred in the anonymizing process (i.e. maximize data …
  • Cited by 5 (1 self) – Add To MetaCart
  • DCMP: A Distributed Cycle Minimization Protocol for Peer-to-Peer Networks  
  • by Zhenzhou Zhu, Panos Kalnis, Spiridon Bakiras
  • …Abstract—Broadcast-based peer-to-peer (P2P) networks, including flat (for example, Gnutella) and two-layer superpeer implementations (for example, Kazaa), are extremely popular nowadays due to their simplicity, ease of deployment, and versatility. The unstructured network topology, however, contains…
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  • Evaluation of top-k OLAP queries using aggregate R-trees  
  • by Nikos Mamoulis, Spiridon Bakiras, Panos Kalnis — 2005 — Proceedings of the International Symposium on Spatial and Temporal Databases (SSTD 2005), Angra dos Reis
  • …Abstract. A top-k OLAP query groups measures with respect to some abstraction level of interesting dimensions and selects the k groups with the highest aggregate value. An example of such a query is “find the 10 combinations of product-type and month with the largest sum of sales”. Such queries may …
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  • Indexing Spatio-Temporal Data Warehouses  
  • by Dimitris Papadias, Yufei Tao, Panos Kalnis, Jun Zhang — 2001 — Proc. of ICDE
  • …Spatio-temporal databases store information about the positions of individual objects over time. In many applications however, such as traffic supervision or mobile communication systems, only summarized data, like the average number of cars in an area for a specific period, or phones serviced by a …
  • Cited by 31 (6 self) – Add To MetaCart
  • Anonymity in Unstructured Data  
  • by Manolis Terrovitis, Nikos Mamoulis, Panos Kalnis
  • …In this paper we study the problem of protecting privacy in the publication of set-valued data. Con-sider a collection of transactional data that contains detailed information about items bought together by individuals. Even after removing all personal characteristics of the buyer, which can serve a…
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  • Efficient OLAP Operations in SPatial Data Warehouses  
  • by Dimitris Papadias, Panos Kalnis, Jun Zhang, Yufei Tao — 2001 — In: Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
  • …Spatial databases store information about the position of individual objects in space. In many applications however, such as traffic supervision or mobile communications, only summarized data, like the number of cars in an area or phones serviced by a cell, is required. Although this information …
  • Cited by 17 (7 self) – Add To MetaCart
  • On discovering moving clusters in spatio-temporal data  
  • by Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras — 2005 — In SSTD
  • …Abstract. A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars moving in a city, etc. We study the discovery of moving clusters in a database of object trajectories. The differenc…
  • Cited by 19 (0 self) – Add To MetaCart
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