Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/66565

The Summarization of Arabic News Texts Using Probabilistic Topic Modeling for L2 Micro Learning Tasks

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dc.contributor.author Elsayed, Issa
dc.date.accessioned 2020-03-18T01:33:03Z
dc.date.available 2020-03-18T01:33:03Z
dc.date.issued 2020-01-14
dc.identifier.uri http://hdl.handle.net/10125/66565
dc.description Report submitted as a result, in part, of participation in the Language Flagship Technology Innovation Center's Summer internship program in Summer 2019.
dc.description.abstract The field of Natural Language Processing (NLP) combines computer science, linguistic theory, and mathematics. Natural Language Processing applications aim at equipping computers with human linguistic knowledge. Applications such as Information Retrieval, Machine Translation, spelling checkers, as well as text sum- marization, are intriguing fields that exploit the techniques of NLP. Text summariza- tion represents an important NLP task that simplifies various reading tasks. These NLP-based text summarization tasks can be utilized for the benefits of language acquisition.
dc.description.sponsorship Language Flagship Technology Innovation Center
dc.format.extent 48 pages
dc.language.iso en-US
dc.rights Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
dc.subject Computational linguistics
dc.subject natural language processing
dc.subject Human Language and Technology
dc.subject.lcsh Natural language processing (Computer science)
dc.title The Summarization of Arabic News Texts Using Probabilistic Topic Modeling for L2 Micro Learning Tasks
dc.type Technical Report
dc.type.dcmi Text
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