An Arabic Question-Answering system for factoid questions

被引：0

作者：

Brini, Wissal ^{[1
]}

Ellouze, Mariem ^{[1
]}

Mesfar, Slim ^{[2
]}

Belguith, Lamia Hadrich ^{[1
]}

机构：

[1] FSEGS Univ Sfax, LARIS MIRACL, Sfax, Tunisia

[2] Univ El Manar, ISI, Tunis, Tunisia

来源：

IEEE NLP-KE 2009: PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND KNOWLEDGE ENGINEERING | 2009年

关键词：

Arabic language; fadoid questions; Natural language processing; Question-Answering system;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose an Arabic Question-Answering (Q-A) system called QASAL "Question -Answering system for Arabic Language". QASAL accepts as an input a natural language question written in Modern Standard Arabic (MSA) and generates as an output the most efficient and appropriate answer. The proposed system is composed of three modules: A question analysis module, a passage retrieval module and an answer extraction module. To process these three modules we use the NooJ Platform which represents a linguistic development environment.

引用

页码：417 / +

页数：3

共 50 条

[21] A question-answering system using argumentation
Moreale, E
Vargas-Vera, M
MICAI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2004, 2972 : 400 - 409
[22] A systematic review of question answering systems for non-factoid questions
Cortes, Eduardo Gabriel
Woloszyn, Vinicius
Barone, Dante
Moeller, Sebastian
Vieira, Renata
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2022, 58 (03) : 453 - 480
[23] Wedding Dress Question-Answering System
Liu, Yiwei
Zhang, Yizhuo
Wei, Yu-Chih
Chen, Chi-Hua
2020 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TAIWAN), 2020,
[24] An analysis of the AskMSR question-answering system
Brill, E
Dumais, S
Banko, N
PROCEEDINGS OF THE 2002 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, 2002, : 257 - 264
[25] Question-answering system for combustion kinetics
Pascazio, Laura
Tran, Dan
Rihm, Simon D.
Bai, Jiaru
Mosbach, Sebastian
Akroyd, Jethro
Kraft, Markus
PROCEEDINGS OF THE COMBUSTION INSTITUTE, 2024, 40 (1-4)
[26] Question-Answering System with Linguistic Summarization
To, Nhuan D.
Reformat, Marek Z.
Yager, Ronald R.
IEEE CIS INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS 2021 (FUZZ-IEEE), 2021,
[27] RAPPORT - A Portuguese Question-Answering System
Rodrigues, Ricardo
Gomes, Paulo
PROGRESS IN ARTIFICIAL INTELLIGENCE-BK, 2015, 9273 : 771 - 782
[28] The Research and Design of Question-Answering System
Song, Bo
Zhuo, Yue
FUZZY SYSTEMS AND DATA MINING III (FSDM 2017), 2017, 299 : 231 - 237
[29] A Study of Deep Learning for Factoid Question Answering System
Day, Min-Yuh
Kuo, Yu-Ling
2020 IEEE 21ST INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE (IRI 2020), 2020, : 419 - 424
[30] Multi-Label Question Classification for Factoid and List Type Questions in Biomedical Question Answering
Wasim, Muhammad
Mahmood, Waqar
Asim, Muhammad Nabeel
Ghani, Muhammad Usman
IEEE ACCESS, 2019, 7 : 3882 - 3896

← 1 2 3 4 5 →