Notes on codes, projects and everything
Semantic Web always sounds like some magic power stuff that a group of people keep yelling about. Chances are, if one is into web development, he/she would have heard of it somehow or other. However, despite the supposedly wide awareness about it, are we using it? Or rather, am I publishing enough data to Semantic Web? OK, I don’t, but why?
Just managed to migrate all my blog sites to one centralized multi-site, so no more half-baked solution and hopefully this brings better plugin compatibility. I have not check with other related services (like Google Webmaster Tools) whether this cause any breakage though. Well, the main purpose of this blog post is actually a draft of what I did for the past two months for my postgraduate programme. Yea, I should have posted more stuff to this blog (just realized that my last post here is already like half a year ago).
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.
Just a quick update to the previous post, the virtuoso storage engine works with redland provided the required packages are properly installed (yes, yes, yes, I know I haven’t release my PHP OO wrapper for Redland). Now that the package is installed, we need to do some configuration so that Redland can use it.
In the previous post, I re-implemented Annoy in 2D with some linear algebra maths. Then I spent some time going through some tutorial on vectors, and expanded the script to handle data in 3D and more. So instead of finding gradient, the perpendicular line in the middle of two points, I construct a plane, and find the distance between it and points to construct the tree.
I came across a video on Youtube on Pi day. Coincidently it was about estimating the value of Pi produced by Matt Parker aka standupmaths. While I am not quite interested in knowing the best way to estimate Pi, I am quite interested in the algorithm he showed in the video however. Specifically, I am interested to find out how easy it is to implement in Python.