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Sakti Pramanik

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Publications by Sakti Pramanik (bibliography)

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2010
 
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Kolbe, Dashiell, Zhu, Qiang and Pramanik, Sakti (2010): Efficient k-nearest neighbor searching in nonordered discrete data spaces. In ACM Transactions on Information Systems, 28 (2) p. 7.

Numerous techniques have been proposed in the past for supporting efficient k-nearest neighbor (k-NN) queries in continuous data spaces. Limited work has been reported in the literature for k-NN queries in a nonordered discrete data space (NDDS). Performing k-NN queries in an NDDS raises new challenges. The Hamming distance is usually used to measure the distance between two vectors (objects) in an NDDS. Due to the coarse granularity of the Hamming distance, a k-NN query in an NDDS may lead to a high degree of nondeterminism for the query result. We propose a new distance measure, called Granularity-Enhanced Hamming (GEH) distance, which effectively reduces the number of candidate solutions for a query. We have also implemented k-NN queries using multidimensional database indexing in NDDSs. Further, we use the properties of our multidimensional NDDS index to derive the probability of encountering valid neighbors within specific regions of the index. This probability is used to develop a new search ordering heuristic. Our experiments on synthetic and genomic data sets demonstrate that our index-based k-NN algorithm is efficient in finding k-NNs in both uniform and nonuniform data sets in NDDSs and that our heuristics are effective in improving the performance of such queries.

© All rights reserved Kolbe et al. and/or ACM Press

2006
 
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Qian, Gang, Zhu, Qiang, Xue, Qiang and Pramanik, Sakti (2006): A space-partitioning-based indexing method for multidimensional non-ordered discrete data spaces. In ACM Transactions on Information Systems, 24 (1) pp. 79-110.

There is an increasing demand for similarity searches in a multidimensional non-ordered discrete data space (NDDS) from application areas such as bioinformatics and data mining. The non-ordered and discrete nature of an NDDS raises new challenges for developing efficient indexing methods for similarity searches. In this article, we propose a new indexing technique, called the NSP-tree, to support efficient similarity searches in an NDDS. As we know, overlap causes a performance degradation for indexing methods (e.g., the R-tree) for a continuous data space. In an NDDS, this problem is even worse due to the limited number of elements available on each dimension of an NDDS. The key idea of the NSP-tree is to use a novel discrete space-partitioning (SP) scheme to ensure no overlap at each level in the tree. A number of heuristics and strategies are incorporated into the tree construction algorithms to deal with the challenges for developing an SP-based index tree for an NDDS. Our experiments demonstrate that the NSP-tree is quite promising in supporting efficient similarity searches in NDDSs. We have compared the NSP-tree with the ND-tree, a data-partitioning-based indexing technique for NDDSs that was proposed recently, and the linear scan using different NDDSs. It was found that the search performance of the NSP-tree was better than those of both methods.

© All rights reserved Qian et al. and/or ACM Press

2005
 
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Xue, Qiang, Pramanik, Sakti, Qian, Gang and Zhu, Qiang (2005): The Hybrid Digital Tree: A New Indexing Technique for Large String Databases. In: Chen, Chin-Sheng, Filipe, Joaquim, Seruca, Isabel and Cordeiro, Josť (eds.) ICEIS 2005 - Proceedings of the Seventh International Conference on Enterprise Information Systems May 25-28, 2005, Miami, USA. pp. 115-121.

 
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Changes to this page (author)

16 Jan 2011: Modified
25 Aug 2009: Modified
23 Jun 2007: Added

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Page maintainer: The Editorial Team
URL: http://www.interaction-design.org/references/authors/sakti_pramanik.html
Jul 28

A user will find any interface design intuitive...with enough practice.

-- Popular computer one-liner

 
 

Featured chapter

Marc Hassenzahl explains the fascinating concept of User Experience and Experience Design. Commentaries by Don Norman, Eric Reiss, Mark Blythe, and Whitney Hess

User Experience and Experience Design !

 
 

Our Latest Books

Kumar and Herger 2013: Gamification at Work: Designing Engaging Business Software...
by Janaki Mythily Kumar and Mario Herger

 
Start reading

Whitworth and Ahmad 2013: The Social Design of Technical Systems: Building technologies for communities...
by Brian Whitworth and Adnan Ahmad

 
Start reading

Soegaard and Dam 2013: The Encyclopedia of Human-Computer Interaction, 2nd Ed....
by Mads Soegaard and Rikke Friis Dam

 
Start reading
 
 

Help us help you!