Browsing by Author "Badaro, Gilbert"
Now showing items 1-6 of 6
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A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models
( Association for Computational Linguistics (ACL) , 2017 , Conference Paper)Opinion mining in Arabic is a challenging task given the rich morphology of the language. The task becomes more challenging when it is applied to Twitter data, which contains additional sources of noise, such as the use ... -
A light lexicon-based mobile application for sentiment mining of arabic tweets
( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)Most advanced mobile applications require server-based and communication. This often causes additional energy consumption on the already energy-limited mobile devices. In this work, we provide to address these limitations ... -
A multiresolution approach to Recommender systems
( Association for Computing Machinery, Inc , 2014 , Conference Paper)Recommender systems face performance challenges when dealing with sparse data. This paper addresses these challenges and proposes the use of Harmonic Analysis. The method provides a novel approach to the user-item matrix ... -
AROMA: A recursive deep learning model for opinion mining in Arabic as a low resource language
( Association for Computing Machinery , 2017 , Article Review)While research on English opinion mining has already achieved significant progress and success, work on Arabic opinion mining is still lagging. This is mainly due to the relative recency of research efforts in developing ... -
Deep learning models for sentiment analysis in arabic
( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input ... -
Recommender systems using harmonic analysis
( IEEE Computer Society , 2015 , Conference Paper)Recommender systems provide recommendations on variety of personal activities or relevant items of interest. They can play a significant role for E-commerce and in daily personal decisions. However, existing recommender ...