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monthly automobile sales using sentiment and topical keyword frequencies related to the target brand over time on social media. Our predictive model illustrates how different time scale-based predictors derived from sentiment and topical keyword frequencies can improve the prediction of the future sales.
paper also provides a search feature to searching the highest similarity of historical information, using text-mining and clustering methods. This makes it easier for users to learning historical event. We compare result of our idea into several device and several keyword to searching history. The experimental result show
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.