SINAI at VideoCLEF 2009

This paper describes the second participation of the SINAI research group in the VideoCLEF track. This year we only participated in the subject classification task. A training collection was generated using the data provided by the VideoCLEF organi-zation. Over this data, a supervised learning approach to classify the test videos was conducted. We have used Support Vector Machines (SVM) as classification algorithm and two experiments have been submitted, using the metadata files and without using them, during the generation of the training corpus. The results obtained show the expected increase in precision due to the use of metadata in the classification of the test videos