LACS 6ystem $nalysis on 5etrieval 0odels for the MediaEval 2014 Search and Hyperlinking Task

We describe the LACS submission to the Search sub-task of the Search and Hyperlinking Task at MediaEval 2014. Our experiments investigate how different retrieval models interact with word stemming and stopword removal. On the development data, we segment the subtitle and Automatic Speech Recognition (ASR) transcripts into fixed length time units, and examine the effect of different retrieval models. We find that stemming provides consistent improvement; stopword removal is more sensitive to the retrieval models on the subtitles. These manipulations do not contribute to stable improvement on the ASR transcripts. Our experiments on test data focus on the subtitle. The gap in performance for different retrieval models is much less compared to the development data. We achieved 0.477 MAP on the test data. 1