2011 September

• Sorting Multilingual Data

  Been trying my best to stick to the well-known UNIX Philosophy – “Do one thing and do it well”, so I have been breaking down my projects into numerous pieces of small tasks and rely on existing tools whenever possible. One of the existing tool that I use a lot is the GNU sort tool. Generally sort utility is really doing fine and dandy without having to configure anything, at least not until I realize the problem that leads to this post.

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Random Posts

• Quick experiment, boosting vs annoy

  While following through the Statistical Learning course, I came across this part on doing regression with boosting. Then reading through the material, and going through it makes me wonder, the same method may be adapted to Erik Bernhardsson‘s annoy algorithm.

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• Further Hack on the Multi-Dimensional Approximate Neighbour Search

  Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.

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• Writing jQuery Plugin 101

  I often struggle to get my Javascript code organized, and have tried numerous ways to do so. I have tried putting relevant code into classes and instantiate as needed, then abuse jQuery’s data() method to store everything (from scalar values to functions and callbacks). Recently, after knowing (briefly) how a jQuery plugin should be written, it does greatly simplify my code.

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• The Little Pythoner, Part 3

  Previously, I started practising recursions by implementing a type check on lat (list of atoms), and ismember (whether an atom is a member of a given lat). Then in the third chapter, named “Cons the Magnificent”, more list manipulation methods are being introduced.

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• Fuzzy C-Means and Content Recommendation

  This post is purely based on my own speculation as there’s no experiment on real-life data to actually back the arguments. I am currently trying to document down a plan for my experiment(s) on recommender system (this reminds me that I have not release the Flickr data collection tool :/) and my supervisor advised to write a paragraph or two on some of the key things. Since he is not going to read it, so I might as well just post it here as a note.

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