Automatic Identification of Arabic expressions related to future events in Lebanon's economy
This addresses the need for automated analysis of economic forecasts in Arabic for Lebanon, but it is incremental as it applies existing NLP tools to a new domain-specific dataset.
The paper tackles the problem of automatically identifying future economic events in Lebanon from Arabic texts by building a corpus, studying linguistic expressions, and developing a method using SLCSAS and AlKhalil Morpho Sys, with validation showing promising results.
In this paper, we propose a method to automatically identify future events in Lebanon's economy from Arabic texts. Challenges are threefold: first, we need to build a corpus of Arabic texts that covers Lebanon's economy; second, we need to study how future events are expressed linguistically in these texts; and third, we need to automatically identify the relevant textual segments accordingly. We will validate this method on a constructed corpus form the web and show that it has very promising results. To do so, we will be using SLCSAS, a system for semantic analysis, based on the Contextual Explorer method, and "AlKhalil Morpho Sys" system for morpho-syntactic analysis.