Notes on codes, projects and everything
Information Retrieval
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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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Approximate Neighbour Search in Multiple Dimensions
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.
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Re-implementing Approximate Nearest Neighbour Search
Recently I switched my search code to Annoy because the input dataset is huge (7.5mil records with 20k dictionary count). It wasn’t without issues though, however I would probably talk about it next time. In order to figure out what each parameters meant, I spent some time watching through the talk given by the author @fulhack.
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Information Retrieving with ….. a lot of libraries
Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.
Random Posts
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Random Data Generator and Reader
Another day, another programming assessment test. This time I was asked to generate some random data, then examine them to get their data type. Practically it is not a very difficult thing to do and I could probably complete it in fewer lines. I am pretty sure there are better ways to do this, as usual though.
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Linked Data Principle
Semantic Web is not just about putting data on the web, but also making links to allow a person as well as a machine to explore the web of data. Links are made in the web of data connects arbitrary things together as described by RDF as opposed to links in the web of hypertext, where links connects to only web-resources. Linkage of arbitrary things then allow related things to be found while performing search.
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Re-implementing a rule engine in Javascript (Introducing Ruler)
Sometimes, letting a piece of code evolving by itself without much planning does not usually end well. However I was quite pleased with a by-product of it and I am currently formalizing it. So the by-product is some sort of DSL for a rule engine that I implemented to process records. It started as some lambda functions in Python but eventually becomes something else.
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Adding a new settings applet for my daemon
This is basically a small incremental update to my script published here. For some reason, the previous version of the script didn’t really work, so this release should fix the problem. Besides fixing the problem where the daemon did not actually launched at start up, I have added a settings applet for this script as well.
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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).
