Using Web-Intelligence for Excavating the Emerging Meaning of Target-Concepts

Representing meaning is a major challenge facing Web 3.0. However, it is extremely difficult to excavate the meaning of a target concept from textual data as there is no one-to-one correspondence between the textual unit in which the target concept is embedded and the conceptual content that we would like to excavate. In this paper, we propose one possible approach for addressing this challenge, by harvesting the Web for metaphorical relations in which the target concept is an argument. In this paper, we present several preliminary results of "Pedesis" - a novel automated system for excavating the meaning of target concepts - and plan to present at the oral presentation an application of this methodology for identifying depression in free text.