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LITMUS is a real-time online and openly accessible service that collects high quality information on landslide events from social media. This service uses disaster related keywords, such as "landslide" and "mudslide", to analyze messages posted by English speaking users. However, comprehensive coverage of disasters must include multilingual support as there are events that are...
In this paper we propose and evaluate three approaches for automated classification of texts in over 60 languages without the need for a manually annotated dataset in those languages. All approaches are based on the randomized Explicit Semantic Analysis method using multilingual Wikipedia articles as their knowledge repository. We evaluate the proposed approaches by classifying a Twitter dataset in...
Document classification or document categorization is one of the most studied areas in computer science due to its importance. The problem is to assign a document using its text to one or more classes or categories from a predefined set. We propose a new approach for fast text classification using randomized explicit semantic analysis (RS-ESA). It is based on a state of the art approach for word sense...
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