Arabic summarization in Tw
Twitter, an online micro blogs, enables its users to write and read text-based posts known as “tweets”. It became one of the most commonly used social networks. However, an important problem arises is that the returned tweets, when searching for a topic phrase, are only sorted by recency not relevan...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2014-06-01
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| Series: | Ain Shams Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447913001184 |
| _version_ | 1818737701251186688 |
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| author | Nawal El-Fishawy Alaa Hamouda Gamal M. Attiya Mohammed Atef |
| author_facet | Nawal El-Fishawy Alaa Hamouda Gamal M. Attiya Mohammed Atef |
| author_sort | Nawal El-Fishawy |
| collection | DOAJ |
| description | Twitter, an online micro blogs, enables its users to write and read text-based posts known as “tweets”. It became one of the most commonly used social networks. However, an important problem arises is that the returned tweets, when searching for a topic phrase, are only sorted by recency not relevancy. This makes the user to manually read through the tweets in order to understand what are primarily saying about the particular topic. Some strategies were developed for summarizing English micro blogs but Arabic micro blogs summarization is still an active research area. This paper presents a machine learning based solution for summarizing Arabic micro blogging posts and more specifically Egyptian dialect summarization. The goal is to produce short summary for Arabic tweets related to a specific topic in less time and effort. The proposed strategy is evaluated and the results are compared with that obtained by the well-known multi-document summarization algorithms including; SumBasic, TF-IDF, PageRank, MEAD, and human summaries. |
| first_indexed | 2024-12-18T00:57:13Z |
| format | Article |
| id | doaj.art-6b3ed00453cb4c2f90cb56b93557b01e |
| institution | Directory Open Access Journal |
| issn | 2090-4479 |
| language | English |
| last_indexed | 2024-12-18T00:57:13Z |
| publishDate | 2014-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj.art-6b3ed00453cb4c2f90cb56b93557b01e2022-12-21T21:26:29ZengElsevierAin Shams Engineering Journal2090-44792014-06-015241142010.1016/j.asej.2013.11.002Arabic summarization in TwNawal El-Fishawy0Alaa Hamouda1Gamal M. Attiya2Mohammed Atef3Faculty of Electronic Engineering, Menoufia University, Menoufia , EgyptFaculty of Computer Engineering, Al-Azhar University, Cairo, EgyptFaculty of Electronic Engineering, Menoufia University, Menoufia , EgyptFaculty of Computer Engineering, Al-Azhar University, Cairo, EgyptTwitter, an online micro blogs, enables its users to write and read text-based posts known as “tweets”. It became one of the most commonly used social networks. However, an important problem arises is that the returned tweets, when searching for a topic phrase, are only sorted by recency not relevancy. This makes the user to manually read through the tweets in order to understand what are primarily saying about the particular topic. Some strategies were developed for summarizing English micro blogs but Arabic micro blogs summarization is still an active research area. This paper presents a machine learning based solution for summarizing Arabic micro blogging posts and more specifically Egyptian dialect summarization. The goal is to produce short summary for Arabic tweets related to a specific topic in less time and effort. The proposed strategy is evaluated and the results are compared with that obtained by the well-known multi-document summarization algorithms including; SumBasic, TF-IDF, PageRank, MEAD, and human summaries.http://www.sciencedirect.com/science/article/pii/S2090447913001184Social networksTwitterSummarizationSignificanceSimilarityFeature selection |
| spellingShingle | Nawal El-Fishawy Alaa Hamouda Gamal M. Attiya Mohammed Atef Arabic summarization in Tw Ain Shams Engineering Journal Social networks Summarization Significance Similarity Feature selection |
| title | Arabic summarization in Tw |
| title_full | Arabic summarization in Tw |
| title_fullStr | Arabic summarization in Tw |
| title_full_unstemmed | Arabic summarization in Tw |
| title_short | Arabic summarization in Tw |
| title_sort | arabic summarization in tw |
| topic | Social networks Summarization Significance Similarity Feature selection |
| url | http://www.sciencedirect.com/science/article/pii/S2090447913001184 |
| work_keys_str_mv | AT nawalelfishawy arabicsummarizationintw AT alaahamouda arabicsummarizationintw AT gamalmattiya arabicsummarizationintw AT mohammedatef arabicsummarizationintw |