Hidden salting in digital media involves the intentional addition or distortion of content patterns with the purpose of content filtering. We propose a method to detect portions of a digital text source which are invisible to the end user, when they are rendered on a visual medium (like a computer monitor). The method consists of “tapping” into the rendering process and analyzing the rendering commands to identify portions of the source text (plaintext) which will be invisible for a human reader, using criteria based on text character and background colors, font size, overlapping characters, etc. Moreover, text deemed visible (covertext) is reconstructed from rendering commands and then the character reading order is identified, which could differ from the rendering order. The detection and resolution of hidden salting is evaluated on two e-mail corpora, and the effectiveness of this method in spam filtering task is assessed. We provide a solution to a relevant open problem in content filtering applications, namely the presence of tricks aimed at circumventing automatic filters.

This paper provides the results of experiments on the detection of arguments in texts among which are legal texts. The detection is seen as a classification problem. A classifier is trained on a set of annotated arguments. Different feature sets are evaluated involving lexical, syntactic, semantic and discourse properties of the texts. The experiments are a first step in the context of automatically classifying arguments in legal texts according to their rhetorical type and their visualization for convenient access and search.