Notes on codes, projects and everything
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.
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).
After publishing the previous note on setting up my development environment, I find myself spending more time in the CLI (usually via SSH from host). Then I find myself not needing all the GUI apps in a standard Ubuntu desktop environment so I went ahead and set up a new environment based on Ubuntu Quantal server edition beta-1. For some reason my network stopped working and didn’t really want to spend time finding out the cause, so I reinstalled everything again today using the final installer, as well as the updated Virtualbox 4.2.6.
After comparing my own implementation of MVC with CodeIgniter’s, now I’m comparing Kohana’s and Zend’s. I have just shifted from CodeIgniter to Kohana recently in work and is currently learning on how to use Zend Framework to build my web-app. As everybody knows, Zend Framework is more like a collection of library classes than a framework a la Ruby on Rails, using MVC in Zend Framework would require one to begin from bootstrapping stage. However, in Kohana, just like other frameworks, bootstrapping is done by the framework itself so the developer will get an installation that almost just works (after a little bit of configuration).
I am starting to like programming in Javascript, especially after understanding more about how Javascript handles scopes. Surprisingly this take me like a year to figure out how scope is managed. The result of the findings is that I start doing a lot of experiments and discovered more interesting stuff through them.
While JSON is a fine data-interchange format, however it does have some limitations. It is well-known for its simplicity, that even a non-programmer can easily compose a JSON file (but humanity will surprise you IRL). Therefore, it is found almost everywhere, from numerous web APIs, to geospatial data (GeoJSON), and even semantic web (RDF/JSON).
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.