Arabic nlp challenges opportunities
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Arabic NLP: Challenges & Opportunities. Dr. Samir Tartir Scientific Day Faculty of Information Philadelphia University May 15 th 2013. ثمن. علم. قِ. General Information. History (Classical) Arabic has remained unchanged, intelligible and functional for more than fifteen centuries.

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Arabic NLP: Challenges & Opportunities

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Arabic nlp challenges opportunities

Arabic NLP: Challenges & Opportunities

Dr. Samir Tartir

Scientific Day

Faculty of Information

Philadelphia University

May 15th 2013


Arabic nlp challenges opportunities

ثمن


Arabic nlp challenges opportunities

علم


Arabic nlp challenges opportunities

قِ


General information

General Information

  • History

    • (Classical) Arabic has remained unchanged, intelligible and functional for more than fifteen centuries.

  • Strategically important

    • 330 million speakers living in an important region

      • huge oil reserves, sacred sites.

    • 1.4 billion Muslims use in their prayers.

  • Cultural and literary heritage

    • Closely associated with Islam


Distribution

Distribution


Versions

Versions

  • Classical

  • Modern

  • Dialects


Arabic language characteristics

Arabic Language Characteristics

  • Highly structured

  • Highly derivational language

    • Morphology

  • Free word order

  • Modern Arabic lacks diacritics (short vowels)


Example

Example*

*Microsoft Arabic NLP Toolkit (ATK) For Academia in the Arab World Presentation, 11/2012


Arabic language characteristics1

Arabic Language Characteristics

  • Synonymy and confusion of non-standardized terms

    • Thermometer: محر، محرار، مقياس حرارة، ميزان حرارة، ترمومتر

  • Technical translation

    • Hydrometer: جهاز قياس كثافة السوائل

  • Uncle, parent…


Letters

Letters

  • One letter, one sound

  • Letters change shape

  • Hamza

  • No capital letters

  • Can use normalization


Ambiguity

Ambiguity

  • Homographs

    • قدم

  • Internal word structure ambiguity

    • بعقوبة

  • Syntactic ambiguity

    • قابلت مدير البنك الجديد

  • Semantic ambiguity

    • يحب علي احمد اكثر من ابراهيم

  • Anaphoric ambiguity

    • قابل الصحفي الوزير الذي انتقده


Arabic nlp challenges opportunities

NLP

  • Automatic summarization

  • Machine translation

  • Named entity recognition (NER)

  • Natural language generation

  • Natural language understanding

  • Optical character recognition (OCR)

  • Question answering

  • Sentiment analysis

  • Speech recognition

  • Word sense disambiguation

  • Information retrieval (IR)

  • Speech processing

  • Text-to-speech

  • Natural language search

  • Automated essay scoring

  • etc


Question answering

Question Answering**

Hammo et al. QARAB: A Question Answering System to Support the Arabic Language. Workshop on Computational Approaches to Semitic Languages. ACL 2002


Arabic nlp issues

Arabic NLP Issues

  • Lack of tools

  • Lack of linguistic references

  • Lack of training data


Available tools

Available Tools

  • Arabic Treebank

  • Arabic WordNet

    • MySQL database

    • SUMO Ontology

    • Java

  • Microsoft Arabic Toolkit (ATK)


Summary

Summary

  • Arabic is difficult to deal with

  • Progress has been made

  • More work is done on different parts

  • Any progress is valuable

    • Business

    • Personal

    • Governmental


Thank you

Thank you


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