Browsing by Keywords "Clustering"
Now showing items 1-20 of 21
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Balancing energy loads in wireless sensor networks through uniformly quantized energy levels-based clustering
(2010)Clustering is considered a common and an effective method to prolong the lifetime of a wireless sensor network. This paper provides a new insight into the cluster formation process based on uniformly quantizing the residual ... -
Cluster based collaborative filtering with inverted indexing
(Bilkent University, 2005)Collectively, a population contains vast amounts of knowledge and modern communication technologies that increase the ease of communication. However, it is not feasible for a single person to aggregate the knowledge of ... -
Cluster searching strategies for collaborative recommendation systems
(2013)In-memory nearest neighbor computation is a typical collaborative filtering approach for high recommendation accuracy. However, this approach is not scalable given the huge number of customers and items in typical commercial ... -
A cluster-based external plagiarism and parallel corpora detection method
(Bilkent University, 2011)Today different editions and translations of the same literary text can be found. Intuitively such translations that are based on the same literary text are expected to possess significantly similar structure. In the ... -
Clustering spatial networks for aggregate query processing: a hypergraph approach
(Elsevier Ltd, 2008-03)In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques ... -
Data decomposition techniques for parallel tree-based k-means clustering
(Bilkent University, 2002)The main computation in the k-means clustering is distance calculations between cluster centroids and patterns. As the number of the patterns and the number of centroids increases, time needed to complete computations ... -
Disrupted network topology in patients with stable and progressive mild cognitive impairment and alzheimer's disease
(Oxford University Press, 2016)Recent findings suggest that Alzheimer's disease (AD) is a disconnection syndrome characterized by abnormalities in large-scale networks. However, the alterations that occur in network topology during the prodromal stages ... -
Efficiency and effectiveness of query processing in cluster-based retrieval
(Elsevier, 2004)Our research shows that for large databases, without considerable additional storage overhead, cluster-based retrieval (CBR) can compete with the time efficiency and effectiveness of the inverted index-based full search ... -
Efficient successor retrieval operations for aggregate query processing on clustered road networks
(Elsevier Inc., 2010)Get-Successors (GS) which retrieves all successors of a junction is a kernel operation used to facilitate aggregate computations in road network queries. Efficient implementation of the GS operation is crucial since the ... -
EHPBS: Energy harvesting prediction based scheduling in wireless sensor networks
(IEEE Computer Society, 2013)The clustering algorithms designed for traditional sensor networks have been adapted for energy harvesting sensor networks (EHWSN). However, in these algorithms, the intra-cluster MAC protocols to be used were either not ... -
Human activity recognition with different artificial neural network based classifiers
(Institute of Electrical and Electronics Engineers Inc., 2017)Human Activity Recognition is a popular topic of research, with the importance it carries and its limited feature vector, to reach high success rates because of the difficulty faced in classification. With the increase of ... -
Hypergraph models and algorithms for data-pattern-based clustering
(Springer, 2004)In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations ... -
Identification of cancer patient subgroups via pathway based multi-view graph kernel clustering
(Bilkent University, 2017-08)Characterizing patient genomic alterations through next-generation sequencing technologies opens up new opportunities for re ning cancer subtypes. Di erent omics data provide di erent views into the molecular biology of ... -
A link-based storage scheme for efficient aggregate query processing on clustered road networks
(Elsevier Ltd, 2010)The need to have efficient storage schemes for spatial networks is apparent when the volume of query processing in some road networks (e.g., the navigation systems) is considered. Specifically, under the assumption that ... -
On-line new event detection and clustering using the concepts of the cover coefficient-based clustering methodology
(Bilkent University, 2002)In this study, we use the concepts of the cover coefficient-based clustering methodology (C3 M) for on-line new event detection and event clustering. The main idea of the study is to use the seed selection process of ... -
Part family machine group formation problem in cellular manufacturing systems
(Bilkent University, 1989)The first and the most important stage in the design of Cellular Manufacturing (CM) systems is the Part Family Machine Group Formation (PF/MGF) problem. In this thesis, different approaches to the PF/MG-F problem are ... -
Personnel bus routing problem: formulation and solution method
(Bilkent University, 1997)In Uiis ihesiK, wc tackle the problem laced by many comptuiies who ofF(M· tra,iis|)ortation services to their personnel. We would reler to it as the Personnel Bus Houting Problem. The transportation services olfered ... -
Profiling instructional effectiveness to reveal its relationship to learning
(Springer, 2014)The purpose of the present study is to define instructional profiles and investigate the relationship between these profiles and learning indicators such as end-of-semester grades and self-reported amount of learning. ... -
Research issues in peer-to-peer data management
(IEEE, 2007)Data management in Peer-to-Peer (P2P) systems is a complicated and challenging issue due to the scale of the network and highly transient population of peers. In this paper, we identify important research problems in P2P ... -
Unsupervised classification of remotely sensed images using Gaussian mixture models and particle swarm optimization
(2010)Gaussian mixture models (GMM) are widely used for un-supervised classification applications in remote sensing. Expectation-Maximization (EM) is the standard algorithm employed to estimate the parameters of these models. ...
