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Automatic Identification of Arabic expressions related to future events in Lebanon's economy

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arxiv 1805.11603 v1 pith:XLDCQDWQ submitted 2018-05-29 cs.CL

classification cs.CL
keywords arabiceconomyeventsfuturelebanonmethodneedtexts
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Wisdom of the Crowds in Forecasting: Forecast Summarization for Supporting Future Event Prediction

    cs.LG 2025-02 conditional novelty 5.0 of 10

    A survey of crowd-based future event prediction from text, plus a new eight-component data model for representing individual forecast statements.

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