Generic thematic analysis techniques were employed, and the data were organized in a framework that clustered factors linked to rural service as organizational (salary, infrastructure, career) and contextual (housing, children's development, safety).
Hence, we design a framework, whereby clustering algorithms incorporating buffer replacement cache behaviour can be conveniently employed for enhancing the I/O performance of OODBMS.
The Hierarchical Dirichlet process (HDP) is a framework for clustering of observations when the observations are present in groups.
The method presented so far describes a framework for clustering genes (time series) using their topological proximity in terms of Granger causality.
Whereas the above papers propose a supervised classification framework, clustering is one of the main tools used to analyze gene expression data obtained from microarray experiments [ 48].
In previous work [10], authors tried to remove the heterogeneity in road accident data using data mining techniques and used a framework using clustering and association rule mining techniques that is capable to remove the heterogeneity from road accident data.
In order to overcome this limitation, we developed a framework to cluster genes by their topological proximity using the time series gene expression information.
To place the components of the IGF signalling pathway into a myogenic framework, we clustered their expression during myotube maturation with those of the MRFs, MEF2A and Pax7.
Hu, Xie, Lin, Wang, and Yu in "Clustering Embedded Approach for Efficient Network Inference" focus on the problem of analyzing information diffusion in social networks and present a framework based on clustering techniques.
Hadighi et al. (2013) proposed a framework based on clustering algorithm for strategic formulation of corporate organization.
