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

File Size Format  
hlt_report_issa.pdf 2.67 MB Adobe PDF View/Open

Item Summary

Title:The Summarization of Arabic News Texts Using Probabilistic Topic Modeling for L2 Micro Learning Tasks
Authors:Elsayed, Issa
Keywords:Computational linguistics
natural language processing
Human Language and Technology
LC Subject Headings:Natural language processing (Computer science)
Date Issued:14 Jan 2020
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.
Description:Report submitted as a result, in part, of participation in the Language Flagship Technology Innovation Center's Summer internship program in Summer 2019.
Pages/Duration:48 pages
URI:http://hdl.handle.net/10125/66565
Rights:Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
http://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections: Reports


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons