2015 April

• Dragon Curve

  I really don’t know how to start explaining what is a Dragon Curve. However, I find it is interesting enough after finding out that there’s actually a fixed pattern of occurrence. Therefore I spent some time writing a series of scripts to plot the generated fractal into a graph. What I didn’t expect is, the series get really complicated after a while.

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Random Posts

• Collaborative Tagging & Folksonomy

  Folksonomy is a neologism of two words, ’folk’ and ’taxonomy’ which describes conceptual structures created by users ^{[4, 5]}. A folksonomy is a set of unstructured collaborative usage of tags for content classification and knowledge representation that is popularized by Web 2.0 and social applications ^{[1, 5]}. Unlike taxonomy that is commonly used to organize resources to form a category hierarchy, folksonomy is non-hierarchical and non-exclusive ^[3]. Both content hierarchy and folksonomy can be used together to better content classification.

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• It’s game time!

  A new day, and a new post on job application. So this time instead of asking a snippet, I was actually asked to deliver some sort of a full application. Not sure why this was required, but I had fun creating them nonetheless. Though I would say I am not really a fan of creating visual stuff though (oh the crappy animation nearly killed me).

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• Revisiting semantic web (plus wheel building with Poetry)

  Back then, when I was still working on my postgraduate degree research, I used RDF, which was the preferred format in the world of Semantic Web to represent data. I eventually dropped the degree, and stopped following the development of the related technology and standards. Until I volunteered to update the import script for popit when I was looking for the next job/project.

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• Quick and Dirty way to manage my VIM config

  Not sure about the others, but the obsession to my coding tools is probably more than I would admit. I have just managed to do a dirty quick hack to manage my VIM configuration settings. While I am sure there are other people doing this, I would like to show my reinvented wheels.

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• Random notes on Pandas and Scikit-learn

  So I first heard about Panda probably a year ago when I was in my previous job. It looked nice, but I didn’t really get the chance to use it. So practically it is a library that makes data looks like a mix of relational database table and excel sheet. It is easy to do query with it, and provides a way to process it fast if you know how to do it properly (no, I don’t, so I cheated).

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