In this paper we address the problem of discovering word semantic similarities via statistical processing of text corpora. We propose a knowledge-poor method that exploits the sentencial context of words for extracting similarity relations between them as well as semantic in nature word clusters. The approach aims at full portability across domains and languages and therefore is based on minimal resources. 1 Motivation Providing digital computers with the capability to acquire conceptual relations between lexical items by processing real-life text corpora is not only an exciting research activity but also a significant task in the framework of many NLP systems. Specifically: