Search Results for author:
Found 14 papers, 0 papers with code
CENTEMENT at SemEval-2018 Task 1: Classification of Tweets using Multiple Thresholds with Self-correction and Weighted Conditional Probabilities
In this paper we present our contribution to SemEval-2018, a classifier for classifying multi-label emotions of Arabic and English tweets.
Using English Dictionaries to generate Commonsense Knowledge in Natural Language
In this paper, we applied this mechanism using two dictionaries: The MacMillan Dictionary and WordNet definitions.
Universal Dependencies for Arabic Tweets
To facilitate cross-lingual studies, there is an increasing interest in identifying linguistic universals.
A Hybrid System to apply Natural Language Inference over Dependency Trees
This system combines two non-deterministic algorithms: the approximate matching from the shallow approach and a theorem prover from the deep approach for handling multi-step inference tasks.
Arabic Tweets Treebanking and Parsing: A Bootstrapping Approach
In this paper, we propose using a {``}bootstrapping{''} method for constructing a dependency treebank of Arabic tweets.
Unsupervised Stemmer for Arabic Tweets
Stemming is an essential processing step in a wide range of high level text processing applications such as information extraction, machine translation and sentiment analysis.
Fast and Robust POS tagger for Arabic Tweets Using Agreement-based Bootstrapping
Part-of-Speech(POS) tagging is a key step in many NLP algorithms.
Supporting Language Learners with the Meanings Of Closed Class Items
The process of learning the Arabic for office is (mktb) is relatively simple and should be possible by means of simple repetition of the word.
Natural Language Inference for Arabic Using Extended Tree Edit Distance with Subtrees
We have extended the standard tree edit distance algorithm to deal with subtree transformation operations as well as single nodes.
