scholarly journals DATA AGGREGATION TECHNIQUE USING GENETIC ALGORITHM

2018 ◽  
Vol 5 (02) ◽  
Keyword(s):  
Genetic Algorithm ◽  
Data Aggregation ◽  
Aggregation Technique

scholarly journals A Genetic Algorithm Approach for Group Recommender System Based on Partial Rankings

2018 ◽  
Vol 29 (1) ◽  
pp. 653-663 ◽  
Author(s):  
Ritu Meena ◽  
Kamal K. Bharadwaj
Keyword(s):  
Genetic Algorithm ◽  
Recommender Systems ◽  
Rank Aggregation ◽  
Partial Ranking ◽  
Novel Approach ◽  
Kendall Tau Distance ◽  
Ultimate Objective ◽  
Aggregation Technique ◽  
The Individual ◽  
Group Recommender

Abstract Many recommender systems frequently make suggestions for group consumable items to the individual users. There has been much work done in group recommender systems (GRSs) with full ranking, but partial ranking (PR) where items are partially ranked still remains a challenge. The ultimate objective of this work is to propose rank aggregation technique for effectively handling the PR problem. Additionally, in real applications, most of the studies have focused on PR without ties (PRWOT). However, the rankings may have ties where some items are placed in the same position, but where some items are partially ranked to be aggregated may not be permutations. In this work, in order to handle problem of PR in GRS for PRWOT and PR with ties (PRWT), we propose a novel approach to GRS based on genetic algorithm (GA) where for PRWOT Spearman foot rule distance and for PRWT Kendall tau distance with bucket order are used as fitness functions. Experimental results are presented that clearly demonstrate that our proposed GRS based on GA for PRWOT (GRS-GA-PRWOT) and PRWT (GRS-GA-PRWT) outperforms well-known baseline GRS techniques.

The Gamification in Education, Healthcare, and Industry

2021 ◽  
pp. 206-232
Author(s):  
Puvvadi Baby Maruthi
Keyword(s):  
Data Aggregation ◽  
Mobile Element ◽  
Mobile Node ◽  
Base Station ◽  
Sensor Nodes ◽  
Aggregated Data ◽  
Three Layer Architecture ◽  
Save Energy ◽  
Aggregation Technique ◽  
Entire Network

Wireless sensor networks (WSN) consist of large numbers of sensor nodes, which are limited in battery power and communication range and have multi-modal sensing capabilities. In this chapter, energy-efficient data aggregation technique is proposed to improve the lifetime of the sensor. Here, the author has used three layer architecture by deploying mobile element/node, which can periodically visit cluster heads (CHs) at which first level data aggregation has been applied to eliminate redundancy. After collecting data from all CHs, mobile element itself will perform second level of data aggregation to eliminate further redundancy. After collecting data from CHs, mobile element will move towards base station/sink and transmits data to base station/sink in order to save energy of entire network. Here, the author has made an attempt to prove that in WSN during data gathering if mobile elements are used to collect the aggregated data from CHs, energy consumption of the entire network will be reduced. The proposed data aggregation with mobile node helps in improving the lifetime of the WSN.

A Lightweight Secure Data Aggregation Technique for Wireless Sensor Network

2014 ◽  
Author(s):  
Sk. Md. Mizanur Rahman ◽  
Mohammad Anwar Hossain ◽  
Maqsood Mahmud ◽  
Muhammad Imran Chaudry ◽  
Ahmad Almogren ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Secure Data ◽  
Secure Data Aggregation ◽  
Aggregation Technique
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