The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we focus on the issue of the m-closest keywords (mCK) query over spatial data in the Web. The mCK query is a problem to find the optimal set of records in the sense that they are the spatially-closest records that satisfy m user-given keywords. The mCK query was proposed by Zhang et al[1]. They assumed
for developing an efficient political chatterbot. We set our study in the context of 2016 Brexit referendum. We argue that employing a subjectivity detector and an emotion analyzer, in addition to the keyword based topic detector, enhances the intent detection process. Next, we discuss the importance of maintaining
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%.
present a more informative result compared to conventional search engine. To valid our method, we developed the TCOND system (Twitter Conversation Detector) which offers an alternative, results to keyword search on twitter and Google. We have evaluated our method on collected social network corpus related to specific
. GeoContext includes methods for filtering a social media stream by keywords and location coordinates in order to provide more specific topics. GeoContext includes a geolocation module, called GeoContext Locator, for predicting the locations of tweets that are not associated with explicit coordinates, in order to model topics in
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.