Future Work Distributed algorithms Key moment detection
{"Image DocumentName": "Future Work Distributed algorithms Key moment detection", "Image ImageDescription": "Key moment of a measure over an EGS: the moment at which the measure score changes dramatically. FVF works with a parameter alpha to control the clustering. Although FVF works well over a wide range of alpha values, the performance of FVF varies not unnoticeably with alpha. To reduce the impact of alpha on FVF, we can try a hierarchal clustering algorithm in preprocessing phase. Our algorithms work on a single computer and all data are stored in main memory. The graphs are becoming larger and larger, which will make a single computer could not efficiently answer queries and make the graph data unable to fit in main memory. One possible direction of future work is to extend the algorithms to work efficiently on hard disk or work distributedly. Key moments of a measure over an EGS are those moments at which the measure score changes dramatically. People are interested at them. Currently, to detect key moments, we compute a measure on every snapshot. Another direction of future work is to detect key moments without computing the measure on each snapshot.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}