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README.yml
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README.yml
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---
owner:
hid: 209
name: Han, Wenxuan
url: https://github.com/bigdata-i523/hid209
paper1:
abstract: >
To understand data analytic steps in web search, and analyze some of
popular approaches/algorithms (e.g. Hubs, PageRank, etc) within big data
and their application in web search aspect.
author:
- Han, Wenxuan
chapter: Media
hid:
- 209
status: Oct 29 2017 100%
title: Big Data Application in Web Search and Text Mining
url: https://github.com/bigdata-i523/hid209/paper1/paper1.pdf
paper2:
review: Nov 6 2017
abstract: >
This paper will focus on clustering algorithms which developed as a
powerful tool for big data analysis. It will introduce the main clustering
types and analyze some highly used algorithms.
author:
- Han, Wenxuan
chapter: Machine Learning
hid:
- 209
status: 100%
title: Clustering Algorithms in Big Data Analysis
url: https://github.com/bigdata-i523/hid209/paper2/paper2.pdf
project:
review: Dec 4 2017
author:
- Han, Wenxuan
- Liu, Yuchen
- Lu, Junjie
hid:
- 209
- 213
- 214
title: Analysis of Digit Recognizer classification algorithms in big data
abstract: >
Nowadays, Digit Recognizer is becoming more and more important in many
different areas, such as zip code recognizer, banking receipt and balance
sheet. Many technology companies are trying to use Big Data to develop
more efficient and accurate algorithm for Digit Recognizer. This project
uses Digit Recognizer dataset from Kaggle.com. There are more than 42000 samples
in the Dataset. Different algorithms such as kth nearest neighbor (KNN),
logistic regression and DNN (deep neural network) will be implemented on
Digit Recognizer. The performance will be compared with the different size of
data and different algorithm.
url: https://github.com/bigdata-i523/hid209/project/
type: project
status: Dec 04 17 100%
chapter: Machine Learning