In the post we share some basics of classification and clustering in Machine learning. We also review some of the cluster analysis methods and algorithms.
Often we see “invalid data”, “clean data”, “normalize data”. What does it mean as to practical data extraction and how does one deal with that? One shot is better than 1000 words though:
Finding the most similar sentence(s) to a given sentence in a text in less than 40 lines of code 🙂
In this post, we’d like to share some of the most interesting terms that are used in today’s science and IT world. We think you will benefit from getting familiar with these modern tech-age expressions.
This post is a continuation of the previous post on Advertising on the Web and Data mining. Here we conclude by reviewing some basic algorithms for placing ads on the web.
The challenge of effective web advertisement primarily involves placing relevant ads on user requested web pages. Those ads must be relevant to a page receiver, that is relevant to the page context and/or directly to the user. What algorithms are being used for this? What trends are there now in business intelligence and data mining for digital advertisement solutions?