Colored Semantic Networks For Content-Analysis

Abstract

This paper adapts a widespread formalism of Knowledge Representation known in the Al literature as J. Sowa's Conceptual Graphs to the purposes of Content Analysis. It is proposed that instead of nested contexts, negation and modalities could be represented by colouring the links and the nodes of the graphs. This colour-based representation of logic enables the replacement of Sowa's game-theoretical semantics by a matching algorithm. It is also claimed that the resulting 'local' application of negation and modalities is close to the behaviour of negation and adverbs in natural language. Above all, the use of colours restores a unique level in semantic networks. These 'flat' semantic networks are appealing to social scientists because they avoid information redundancy and improve connectivity in the network. Two methods of textual analysis that can take direct benefit from semantic networks (semantic paths distributions and texts clustering) are presented. However, 'flat' semantic networks that remain semantically correct are perhaps even more interesting because they may bridge standard networks with connectionnist networks. In such a perspective, Coloured Conceptual Graphs represent an intermediate but promising step.