Web page classification refers to the problem of automatically assigning a web page to one or moreclasses after analysing its features. Automated web page classifiers have many applications, and many re- searchers have proposed techniques and tools to perform web page classification. Unfortunately, the ex- isting tools have a number of drawbacks that makes them unappealing for real-world scenarios, namely:they require a previous extensive crawling, they are supervised, they need to download a page beforeclassifying it, or they are site-, language-, or domain-dependent. In this article, we propose CALA, a toolfor URL-based web page classification. The strongest features of our tool are that it does not require aprevious extensive crawling to achieve good classification results, it is unsupervised, it is based exclu- sively on URL features, which means that pages can be classified without downloading them, and it issite-, language-, and domain-independent, which makes it generally applicable. We have validated ourtool with 22 real-world web sites from multiple domains and languages, and our conclusion is that CALAis very effective and efficient in practice.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Ciencia e Innovación TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-EMinisterio de Economía y Competitividad TIN2013-40848-
