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enhances the machine learning based Stanford CoreNLP Part-of-Speech (POS) tagger with the Twitter model to extract essential keywords from a tweet. The system was enhanced using two rule-based parsers and a corpus. The research was conducted using tweets of customer service requests sent to a telecommunication company. A
identifying Tweets that describe cases with acute and more critical symptoms from those referring to milder cases. We found that making use of mereley very small n-gram keyword lexica, the automatic identification of critical cases reaches an accuracy of 92%.
Age predictive analysis is to predict the age of the users who posted the message in any microblog. By using some keywords, we extract the messages as dataset and processed for predicting the age of the user. Here, the design and techniques to foreseen the age of the user by microblog dataset are presented. In recent
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.