no code implementations • 9 Apr 2024 • Alessio Ferrari, Sallam Abualhaija, Chetan Arora
Complementing natural language (NL) requirements with graphical models can improve stakeholders' communication and provide directions for system design.
no code implementations • 23 Nov 2023 • Muhammad Ilyas Azeem, Sallam Abualhaija
Our evaluation shows that best-performing solutions yield F2 score of 86. 7% and 89. 7% are based on pre-trained BERT and RoBERTa language models.
no code implementations • 23 Nov 2023 • Sallam Abualhaija, Marcello Ceci, Lionel Briand
Specifically, we describe possible alternatives for creating machine-analyzable representations from regulations, survey the existing automated means for enabling compliance verification against regulations, and further reflect on the current challenges of legal requirements analysis.
no code implementations • 21 Jun 2022 • Saad Ezzini, Sallam Abualhaija, Chetan Arora, Mehrdad Sabetzadeh
We introduce TAPHSIR, a tool for anaphoric ambiguity detection and anaphora resolution in requirements.
no code implementations • 10 Jun 2021 • Orlando Amaral, Sallam Abualhaija, Damiano Torre, Mehrdad Sabetzadeh, Lionel C. Briand
A prerequisite for GDPR compliance checking is to verify whether the content of a privacy policy is complete according to the provisions of GDPR.
no code implementations • RANLP 2017 • Sallam Abualhaija, Nina Tahmasebi, Diane Forin, Karl-Heinz Zimmermann
Word sense disambiguation is defined as finding the corresponding sense for a target word in a given context, which comprises a major step in text applications.
no code implementations • EACL 2017 • Sallam Abualhaija, Tristan Miller, Judith Eckle-Kohler, Iryna Gurevych, Karl-Heinz Zimmermann
In this paper, we propose using metaheuristics{---}in particular, simulated annealing and the new D-Bees algorithm{---}to solve word sense disambiguation as an optimization problem within a knowledge-based lexical substitution system.
no code implementations • 6 May 2014 • Sallam Abualhaija, Karl-Heinz Zimmermann
Word sense disambiguation (WSD) is a problem in the field of computational linguistics given as finding the intended sense of a word (or a set of words) when it is activated within a certain context.