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| Knowledge Discovery Through Data Visualization Of Drive Test Data
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Source |
International Journal of Computer Science and Security (IJCSS) |
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Table of Contents |
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Volume: 3 Issue: 6 |
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Pages: 448-594 |
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Publication
Date: January 2010 |
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ISSN
(Online): 1985-1553 |
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Pages |
559 - 568 |
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Author(s) |
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Published
Date |
19-02-2010 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Mobility Patterns, hand-offs, Drive Test, Mobile phones |
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| This paper focuses on the analysis of a large volume of drive test data and the identification of adverse trends or aberrant behavior of a mobile handset under test by means of drive test data visualization. The first target application was to identify poor mobility decisions that are made by the handsets in calls. The goal was to compare a set of behaviors from a baseline unit (one accepted to generally operate well). We were able to identify a particular call that was exhibiting a different path (talking to a different cell than expected or taking longer to move to a new cell). In this paper we develop a mobility tool that evaluates the handset’s performance by means of mapping the handoffs on the Google Maps. The mapping of the handoffs by means of the Google Maps were very powerful in identifying the above mentioned mobility patterns. |
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O. J. Oyelade and O. O. Oyejoke, “Knowledge Discovery from Students’ Result Repository: Association Rule Mining Approach”, International Journal of Computer Science and Security (IJCSS), 4(2), pp. 199 – 207, 2010. |
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| 2 |
E. Chandra and K. Nandhini, “Knowledge Mining from Student Data”, European Journal of Scientific Research, 47(1), pp.156-163, 2010. |
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science.gov |
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2DIX.COM |
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| Shalini Saxena : Colleagues
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| Abhijit S. Pandya : Colleagues
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| Robert Stone : Colleagues
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| Saeed Rajput : Colleagues
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| Sam Hsu : Colleagues
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