SCISOR: extracting information from on-line news
Communications of the ACM
MURAX: a robust linguistic approach for question answering using an on-line encyclopedia
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Improving relevance feedback in the vector space model
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Building a question answering test collection
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Understanding Natural Language
Understanding Natural Language
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Experiments with open-domain textual Question Answering
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Importance of pronominal anaphora resolution in question answering systems
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The structure and performance of an open-domain question answering system
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Discovering lexical information by tagging Arabic newspaper text
Semitic '98 Proceedings of the Workshop on Computational Approaches to Semitic Languages
Adapting the JIRS Passage Retrieval System to the Arabic Language
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Semitic '09 Proceedings of the EACL 2009 Workshop on Computational Approaches to Semitic Languages
Using some web content mining techniques for Arabic text classification
DNCOCO'09 Proceedings of the 8th WSEAS international conference on Data networks, communications, computers
AraTation: an Arabic semantic annotation tool
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
A comparison study of some Arabic root finding algorithms
Journal of the American Society for Information Science and Technology
Performance of NB and SVM classifiers in Islamic Arabic data
Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications
Automatically finding answers to "Why" and "How to" questions for Arabic language
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
Categorize arabic data sets using multi-class classification based on association rule approach
Proceedings of the 2011 International Conference on Intelligent Semantic Web-Services and Applications
How to extract Arabic definitions from the web? Arabic definition question answering system
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
On the improvement of passage retrieval in Arabic question/answering (Q/A) systems
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Arabic rhetorical relations extraction for answering "why" and "how to" questions
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
On the evaluation and improvement of Arabic WordNet coverage and usability
Language Resources and Evaluation
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We describe the design and implementation of a question answering (QA) system called QARAB. It is a system that takes natural language questions expressed in the Arabic language and attempts to provide short answers. The system's primary source of knowledge is a collection of Arabic newspaper text extracted from Al-Raya, a newspaper published in Qatar. During the last few years the information retrieval community has attacked this problem for English using standard IR techniques with only mediocre success. We are tackling this problem for Arabic using traditional Information Retrieval (IR) techniques coupled with a sophisticated Natural Language Processing (NLP) approach. To identify the answer, we adopt a keyword matching strategy along with matching simple structures extracted from both the question and the candidate documents selected by the IR system. To achieve this goal, we use an existing tagger to identify proper names and other crucial lexical items and build lexical entries for them on the fly. We also carry out an analysis of Arabic question forms and attempt a better understanding of what kinds of answers users find satisfactory. The paucity of studies of real users has limited results in earlier research.