Mohamad Jaber


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Automated Stock Price Prediction Using Machine Learning
Wassim El-Hajj Mariam Mokalled | Mohamad Jaber
Proceedings of the Second Financial Narrative Processing Workshop (FNP 2019)


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TopoText: Interactive Digital Mapping of Literary Text
Randa El Khatib | Julia El Zini | David Wrisley | Mohamad Jaber | Shady Elbassuoni
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations

We demonstrate TopoText, an interactive tool for digital mapping of literary text. TopoText takes as input a literary piece of text such as a novel or a biography article and automatically extracts all place names in the text. The identified places are then geoparsed and displayed on an interactive map. TopoText calculates the number of times a place was mentioned in the text, which is then reflected on the map allowing the end-user to grasp the importance of the different places within the text. It also displays the most frequent words mentioned within a specified proximity of a place name in context or across the entire text. This can also be faceted according to part of speech tags. Finally, TopoText keeps the human in the loop by allowing the end-user to disambiguate places and to provide specific place annotations. All extracted information such as geolocations, place frequencies, as well as all user-provided annotations can be automatically exported as a CSV file that can be imported later by the same user or other users.