ajeb first seminar
TRANSCRIPT
AjebArabic Question Answering System
سج
Project Members
Eid Mosad El-Sayed CS Khaled Ahmed Sayed CS Sarah Abdel Monem Ismail CS
Supervised by: Prof. Dr. Mostafa Aref Dr. Ibrahim Fathy TA. Mohamed Hamdy سج
Agenda
Introduction:• Motivations.
• Problem Definition.
• Objective.
• Challenges.
Survey Summary:• Name Entity Recognition(NER).
• Previous Work.
Ajeb Architecture. Tools. Project Time Plan. References. سج
Introduction
Motivations
Introduction
Motivation
سج Ongoing update & progress in Arabic Natural
Language Processing (ANLP).
Motivation
سج There is still little research in the Arabic
language.
Motivation
سج Arabic is our mother language, so we prefer
the Arabic language over any other one.
Motivation
سج The Arabic language was ranked as the fifth
most important language in the world with 300 million speakers.
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Motivation
سج Arabic is the language of the holy Quran.
Problem Definition
Introduction
Problem Definition
سج The amount of available Arabic information
is becoming very huge.
Problem Definition
سج Search engines are not able to provide an
exact answer.
Problem Definition
سج Lack of time to find a short and precise
answer among the variety of available documents.
Objective
Introduction
Objective
سج Obtaining a brief and concise answer
for Arabic factoid questions extracted from internet corpus.
سج
Challenges
Introduction
Challenges
سج Arabic is highly inflectional and derivational,
which makes morphological analysis a very complex task.
فعلفعول
مفعول فاعل
فعال
Challenges
سج The absence of diacritics (which represent
most vowels) in the written text creates ambiguity.
Challenges
سج
The writing direction is from right-to-left and some of the characters change their shapes based on their location in the word.
Survey Summary
Common Methodology
سجDocuments
Name Entity Recognition (NER)
Name Entity Recognition (NER)
Survey Summary
Name Entity Recognition (NER)
سج
Classify elements in text into predefined categories:• Persons.
• Organizations.
• Locations.
• Dates.
• Quantities, monetary values and percentages.
Name Entity Recognition (NER)
سج
Importance:• Since the Arabic language is very hard to
understand by the computer, NER is been used to make the QA system semi-understand.
Name Entity Recognition (NER)
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What is the problem of recognizing names in the Arabic language?• Non-vocalization.
• Lack of capitalization.
• Delimitation problems.
Previous Work
Survey Summary
Previous Work - QARAB
سج
QARAB finds answers under the following assumptions: The answer exists in a collection of Arabic newspaper
text extracted from the Al-Raya newspaper. All supporting information for the answer lies in one
document . The answer is a short passage.
Ajeb Architecture
Ajeb Architecture
سج
Ajeb Architecture
.Question Analysis (1 سج
Ajeb Architecture
.Passage Retrieval (2 سج
Ajeb Architecture
.Answer Extraction (3 سج
Tools
Tools
سج
Project Time Plan
Project Time Plan
سج
References
سج
[1]Hammo, B., H.Abu-Salem, S.Lytinen and M.Evens, 2002. QARAB: A question answering system to support the Arabic language. Proceedings of the 40th Association for Computational Linguistics on Computational Approaches to Semetic Languages, ACL’02 University of Pennsylvania, PA, USA, 55-65.
[2]Paolo Rosso, Yassine Benajiba, and Abdelouahid Lyhyaoui, "Towards an Arabic Question Answering System" 2007.
[3]Wissal Brini, Mariem Ellouze, Omar Trigui(ANLP Research Group), Slim Mesfar, Lamia Hadrich Belguith, Paolo Rosso, "Factoid and definitional Arabic Question Answering system", 2008.
[4]Saleem Abuleil, "Extracting Names From Arabic Text For Question-Answering Systems", 2003.
