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Reseach Article

Temporal Cluster graphs for visualizing Trends

Published on May 2012 by B. Ratnamala, P. M. Kiran
National Conference on Advances in Computer Science and Applications (NCACSA 2012)
Foundation of Computer Science USA
NCACSA - Number 4
May 2012
Authors: B. Ratnamala, P. M. Kiran
a9affb44-5253-45a6-a363-997c97d9aca7

B. Ratnamala, P. M. Kiran . Temporal Cluster graphs for visualizing Trends. National Conference on Advances in Computer Science and Applications (NCACSA 2012). NCACSA, 4 (May 2012), 17-19.

@article{
author = { B. Ratnamala, P. M. Kiran },
title = { Temporal Cluster graphs for visualizing Trends },
journal = { National Conference on Advances in Computer Science and Applications (NCACSA 2012) },
issue_date = { May 2012 },
volume = { NCACSA },
number = { 4 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 17-19 },
numpages = 3,
url = { /proceedings/ncacsa/number4/6501-1026/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computer Science and Applications (NCACSA 2012)
%A B. Ratnamala
%A P. M. Kiran
%T Temporal Cluster graphs for visualizing Trends
%J National Conference on Advances in Computer Science and Applications (NCACSA 2012)
%@ 0975-8887
%V NCACSA
%N 4
%P 17-19
%D 2012
%I International Journal of Computer Applications
Abstract

Organizations and firms are capturing increasingly more data about their customers, suppliers, competitors and business environment. Most of this data is multidimensional and temporal in nature. Data mining and business intelligence technique are often used to discover in such data. We propose a new data analysis and visualization technique for representing trends and temporal data using K-means clustering based approach. And we introduce a system that implements the temporal clustered graph construct which maps temporal data to a two dimensional directed graph that identifies trends in dominant data types over time. In this paper, we present our temporal clustered based technique and its implementation and performance.

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Index Terms

Computer Science
Information Sciences

Keywords

Clustering Data Knowledge And Visualization Data Mining Temporal Data Mining Trend Analysis