Searching, translating and classifying information in cyberspace

Abstract

In this paper we describe current search technologies available on the web, explain underlying difficulties and show their limits, related to either current technologies or to the intrinsic properties of all natural languages. We then analyze the effectiveness of freely available machine translation services and demonstrate that under certain conditions these translation systems can operate at the same performance levels as manual translators. Searching for factual information with commercial search engines also allows the retrieval of facts, user comments and opinions on target items. In the third part we explain how the principle machine learning strategies are able to classify short passages of text extracted from the blogosphere as factual or opinionated and then classify their polarity (positive, negative or mixed). © 2011 Springer-Verlag Berlin Heidelberg.