Analysis of Dendrogram Tree for Identifying and Visualizing Trends in Multi-attribute Transactional Data
Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2012, Vol 3, Issue 1
Abstract
Most of the data collected by organizations and firms contains multi-attribute and temporal data. Identifying temporal relationships (e.g., trends) in data constitutes an important problem that is relevant in many business and academic settings. Data mining techniques are used to discover patterns in such data. Temporal data can take many forms, most commonly being general transactional (multi)attribute-value data, for which time series or sequence analysis methods are not particularly well suited. In this paper we present the clustering algorithm with performance and implementation of dataset based on distances in miles between US cities.
Authors and Affiliations
D. Radha Rani1 , A. Vini Bharati2 , P. Lakshmi Durga Madhuri3 , M. Phaneendra Babu4 , A. Sravani5
Keywords
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