Topic Detection and Tracking (TDT) research has produced some successful statistical tracking systems. While lexical chaining, a non-statistical approach, has also been applied to the task of tracking by Carthy and Stokes for the 2001 TDT evaluation, an efficient tracking system based on this technology has yet to be developed. In thesis we investigate two new techniques which can improve Carthy's original design. First, at the core of our system is a semantic domain chainer. This chainer relies not only on the WordNet database for semantic relationships but also on Magnini's semantic domain database, which is an extension of WordNet. The domain-chaining algorithm is a linear algorithm. Second, to handle proper nouns, we gather all of the ones that occur in a news story together in a chain reserved for proper nouns. In this thesis we also discuss the linguistic limitations of lexical chainers to represent textual meaning.

This thesis presents a comprehensive study of the Japanese double-ga construction and offers an explanation as to why the Japanese double-ga construction does not allow scrambling. In chapter 2, the particle-ga and the particle-wa are defined as the focus marker and the topic marker respectively. The different shades of meaning that both particles have are also explained. Chapter 3 illustrates the Japanese double -ga construction. Chapter 4 deals with the impossibility of scrambling in the double-particle constructions. A strong parallelism is shown between the double-ga construction and the double-wa construction. The claim is that there are three "pragmatic slots" that the particle-ga and -wa can occupy in the sentence. The rigid-fixed-order of these three slots contributes to the prohibition of scrambling.