PHP/ir

When it comes to classification, and machine learning in general, at the head of the pack there's often a Support Vector Machine based method. In this post we'll look at what SVMs do and how they work, and as usual there's a some example code. However, even a simple PHP only SVM implementation is a little bit long, so this time the complete source is available separately in a zip file. Read More »

So far when we've been looking at text we've been breaking it down into words, albeit with varying degrees of preprocessing, and using the word as our token or term. However, there is quite a lot of mileage in comparing other units of text, for example the letter n-gram, which can prove effective in a variety of applications. Read More »

One of the issues with the boolean search model is that results are unranked - every matching document for a query contains all of the terms in that query, and there's no real way of saying which are 'better'. However, if we could weight the terms in a document based on how representative they were of the document as a whole, we could order our results by the ones that were the best match for the query. This is the idea that forms the basis for the vector space model. Read More »