Notes on codes, projects and everything
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).
A friend of mine recently posted a screenshot containing a code snippet for a fairly straight forward problem. So after reading the solution I suddenly had the itch to propose another solution that I initially thought would be better (SPOILER: Turns out it isn’t). Then mysteriously I stuck myself to my seat and started coding an alternative solution to it instead of playing Diablo 3 just now.
After coded enough Javascript few months back, I found that there are a couple of functions that I kept re-using in different projects. Therefore I took some time to refactor them and re-arrange them into a single file. The common code that I keep reusing even today consists of functions that does prototypical inheritance, scope maintenance, some jquery stuff, google maps api stuff and some general ajax application related code.
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.
Often times one would have to write code to evaluate logical statements. For example, given statement p and q, what is p implies q? As there’s no operator for implication in PHP, one would have to rewrite the statement that consists only in NOT (!), AND (&&) and OR (||) operators. When there are a huge load of these statements, code can be difficult to read.
I was asked to evaluate fuzzy c-means to find out whether it is a good clustering algorithm for my MPhil project. So I spent the whole afternoon reading through some tutorial to get some basic understanding. Then I thought why not implement it in Clojure because it doesn’t look too complicated (I was so wrong…).