Detecting Topic Shifts Using A Cache Memory

The use of cache memories and symmetric Kullback-Leibler distances is proposed for topic classification and topic-shift detection. Experiments with a large corpus of articles from the French newspaper "Le Monde show tangible advantages when different models are combined with a suitable strategy. Experimental results show that different strategies for topic shift detection have to be used depending on whether high recall or high precision are sought. Furthermore, methods based on topic independent distributions provide complementary candidates with respect to the use of topicdependent distributions leading to an increase in recall with a minor loss in precision. 1. INTRODUCTION Statistical methods for topic spotting and the detection of topic shifts are now the object of research efforts because of their potential in important applications [6]. It is also possible to use topic-dependent language models (LM) for improving Automatic Speech Recognition (ASR) [3]. Topic spotting is a de..