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Abstract

Technology always seeks to improve the little details in our lives for a faster and a more efficient life-pace. One of these little problems we face in our daily lives is finding relevant events. For example you visit a place like Katara with your kids and you spend your time in vain looking for a fun event, and after you leave the venue a friend of yours tells you about this interesting “Henna and face painting workshop organized in building 25.”. To solve this problem we propose QEvents. QEvents is a platform that provides users with real-time recommendations about events happening around their location and that best match their preferences. QEvents renders the events in a map-centric dashboard to allow easy browsing and user-friendly interactions. QEvents continuously listens to online channels that broadcast information about events taking place in Qatar, including specialized websites (e.g. eventsdoha.com), social media (e.g. Twitter), and news (e.g. dohanews.com). The main challenge QEvents strives to solve is how to extract important features such as title, location, and time from free text describing the events. We will show in this paper how one could leverage existing technologies such as Topic modeling, Named Entity Recognition, and advanced text parsing to transform a plain event listing website into a dynamic and alive service capable of recognizing events’ location, title, category, as well as starting and ending time, and nicely rendering them in a map-centric visualization allowing a more natural exploration.

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/content/papers/10.5339/qfarc.2018.ICTPD1130
2018-03-15
2020-08-08
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http://instance.metastore.ingenta.com/content/papers/10.5339/qfarc.2018.ICTPD1130
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