Work

Al-Bayan: A Knowledge-based System for Arabic Answer Selection

Year: 2015

Type: conference-paper

Abstract: This paper describes Al-Bayan team participation in SemEval-2015 Task 3, Subtask A. Task 3 targets semantic solutions for answer selection in community question answering systems.We propose a knowledge-based solution for answer selection of Arabic questions, specialized for Islamic sciences.We build a Semantic Interpreter to evaluate the semantic similarity between Arabic question and answers using our Quranic ontology of concepts.Using supervised learning, we classify the candidate answers according to their relevance to the users questions.Results show that our system achieves 74.53% accuracy which is comparable to the other participating systems.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/s15-2040

Authors: Reham Mohamed, Maha Ragab, Heba Abdelnasser, Nagwa M. El-Makky, Marwan Torki

Institution: Alexandria University

Language: English

Topic: Expert finding and Q&A systems

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2250877322

FWCI: 2.607

Cites: 16

Cited by: 16

Related to: 10