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A Survey on Prediction of Missing Sensor Data Using Association Rule

Authors(2):

Hitarth Chauhan, Bakul Panchal
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Missing values is major problem in sensor network. Currently we have many existing approach to predict missing values in stream of data. But for pre fetched existing data we canít use such techniques. So while querying in such data will lead to wrong results. So in this paper we will try to predict such missing data in existing sensor data using association rule mining techniques.

Hitarth Chauhan, Bakul Panchal

Window Association Rule Mining, K-nearest Neighbour Estimation, WSN, Data Reduction Mechanism, Data Mining, Sensor Data

  1. Sneha Arjun Dhargalkar, A.D. Bapat “Determining Missing Values in Dimension Incomplete Databases using Spatial-Temporal Correlation Techniques”, In 2014, IEEE
  2. Mihail Halatchev Le Gruenwald, “Estimating Missing Values in Related Sensor Data Streams” ADVANCES IN DATA MANAGEMENT 2005
  3. Le Gruenwald, Hamed Chok, Mazen Aboukhamis, “Using Data Mining to Estimate Missing Sensor Data” In 2007 IEEE
  4. Anjan Das, “An Enhanced Data Reduction Mechanism to Gather Data for Mining Sensor Association Rules” In 2011 IEEE

Publication Details

Published in : Volume 1 | Issue 6 | November-December - 2015
Date of Publication Print ISSN Online ISSN
2015-12-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
182-184 IJSRSET151639   Technoscience Academy

Cite This Article

Hitarth Chauhan, Bakul Panchal, "A Survey on Prediction of Missing Sensor Data Using Association Rule", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.182-184, November-December-2015.
URL : http://ijsrset.com/IJSRSET151639.php

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