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This research proposes a framework for aspect-based sentiment analysis (ABSA) of Hotels' reviews. The proposed framework consists of: (a) a reference human annotated Arabic dataset to support ABSA tasks such as aspect category identification, opinion target expression extraction, and opinion sentiment polarity. The dataset was annotated on both sentence-level and text-level, (b) baseline approach...
In tweet authentication, we are concerned with correctly attributing a tweet to its true author based on its textual content. The more general problem of authenticating long documents has been studied before and the most common approach relies on the intuitive idea that each author has a unique style that can be captured using stylometric features (SF). Inspired by the success of modern automatic...
Multi-label classification of textual data is an important problem with the growing size of available data and the increasing difficulties in assigning a single label to each piece of text. Examples range from news articles to emails. Most of the existing works consider English text. This work focuses on multi-label classification of Arabic articles. After dataset collection, three multi-label classifiers...
Authorship authentication of a certain text is concerned with correctly attributing it to its author based on its contents. It is a very important problem with deep root in history as many classical texts have doubtful attributions. The information age and ubiquitous use of the Internet is further complicating this problem and adding more dimensions to it. We are interested in the modern version of...
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