IEEE Projects on Python


 
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2018-2019 Python IEEE Projects

IEEE Python Projects 2019 Titles

1. Analysis of Knowledge Sharing Activities on a Social Network Incorporated Discussion Forum: A Case Study of DISboards

2. Characterizing User Connections in Social Media through User-Shared Images

3. Content-Aware Partial Compression for Textual Big Data Analysis in Hadoop

4.Effective Prediction of Missing Data on Apache Spark over Multivariable Time Series

5.Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach

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6. Euler Clustering on Large-Scale Dataset

7. HashTag Erasure Codes: From Theory to Practice

8. Human Activity Recognition with Posture Tendency Descriptors on Action Snippets

9. LS-Decomposition for Robust Recovery of Sensory Big Data

10. Mining the Most Influentialk-Location Set from Massive Trajectories

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11. pg-Causality: Identifying Spatiotemporal Causal Pathways for Air Pollutants with Urban Big Data

12. SecurekNearest Neighbors Query for High-Dimensional Vectors in Outsourced Environments

IEEE python projects 2018

13. SmartQ: A Question and Answer System for Supplying High-Quality and Trustworthy Answers

14.Assembling and Using a Cellular Dataset for Mobile Network Analysis and Planning

15.Sentiment analysis with Twitter DB





2018-2019 ieee projects in Python

IEEE Python 10 Algorithms

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In a world of open data and large-scale measurements, it is often feasible to obtain a real-world trace to fit to one's research problem. Feasible, however, does not imply simple. Taking next-generation cellular network planning as a case study, in this paper we describe a large-scale dataset, combining topology, traffic demand from call detail records, and demographic information throughout a whole country. We investigate how these aspects interact, revealing effects that are normally not captured by smaller-scale or synthetic datasets. In addition to making the resulting dataset available for download, we discuss how our experience can be generalized to other scenarios and case studies, i.e., how everyone can construct a similar dataset from publicly available information.

IEEE python projects 2018



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2018-2019 IEEE Projects on Python Contact: 9591912372


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