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We investigate the problem of processing a large amount of continuous spatial-keyword queries over streaming data, which is essential in many applications such as location-based recommendation and advertising, thanks to the proliferation of geo-equipped devices and the ensuing location-based social media applications
structured (PS) music data, WAV real example (RE) music data and keyword sound (WS) text-information data. Firstly, we introduce our system architecture. Secondly, we propose anew construction method for music feature libraries in order to achieve more satisfactory results. Thirdly, we present and design the novel mix-indexing
it possible to query and make use of social media data in novel ways. In this work, we formulate a novel and useful problem called top-k local user search (TkLUS for short) from tweets with geo-tags. Given a location q, a distance r, and a set of keywords W, the TkLUS query finds the top-k users who have posted tweets
proposed to provide users with a personalized news service. The system takes advantage of the network information crawling, web-based text mining and personalized recommendations technologies to realize automated extraction of news tag. The innovation of this mode is that the tag contains both categories and keywords. It
In this system prototype demonstration we present, Ultimate Course Search (UCS), a learning tool developed to provide students ways to efficiently search electronic educational materials. UCS integrates slides, lecture videos and textbooks into a single platform. The keywords extracted from the textbooks and the
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.