Many natural language processing (NLP) applications require the computation of similarities
between pairs of syntactic or semantic trees. Many researchers have used tree edit distance …

This thesis explores a range of approaches to the task of recognising textual entailment
(RTE), ie determining whether one text snippet entails another, for Arabic, where we are …

A relatively large dataset coupled with efficient but computationally slow machine learning
algorithm poses a great deal of challenge for Internet of Things (IoT). On the contrary, Deep …

A lot of natural language processing (NLP) applications require the computation of
similarities between pairs of syntactic or semantic trees. Tree edit distance (TED), in this …

This paper introduces a method for improving tree edit distance (TED) for textual entailment.
We explore two ways of improving TED: we extend the standard TED to use edit operations …

This paper concentrates on contrasting between two well-known Arabic parsers that is the
Stanford Parser and the Bikel parser by utilizing the Arabic Treebank (ATB). The contrast …

The aim here is to create a dependency treebank from a phrase-structure treebank for
Arabic. Arabic has a number of characteristics, described below, which make it particularly …

A number of trainable dependency parsers have been presented in the literature. These
parsers require tagged input: this may potentially cause a problem, because taggers are not …

In order to understand natural languages, we have to be able to determine the relations
between words, in other words we have to be able to'parse'the input text. This is a difficult …

This thesis focuses on comparing between two famous Arabic parsers Stanford Parser and
Bikel parser using Arabic Treebank (ATB) for model training and testing and for this purpose …