A Survey Study on Relation Extraction for Web Pages
Natural language means a language that is used for communication by human. Natural Language Processing (NLP) helps machines to understand the natural language. The natural language for the web pages consists of many semantic relations between entities. Discovering significant types of relations from...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Arabic |
| Published: |
College of Education for Pure Sciences
2020-03-01
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| Series: | مجلة التربية والعلم |
| Subjects: | |
| Online Access: | https://edusj.mosuljournals.com/article_164377_8c74eecd5a44832b9889278c7d1872a3.pdf |
| _version_ | 1818450903189946368 |
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| author | Ghada Alsaigh Ghayda Al-Talib Alaa Y. Taqa |
| author_facet | Ghada Alsaigh Ghayda Al-Talib Alaa Y. Taqa |
| author_sort | Ghada Alsaigh |
| collection | DOAJ |
| description | Natural language means a language that is used for communication by human. Natural Language Processing (NLP) helps machines to understand the natural language. The natural language for the web pages consists of many semantic relations between entities. Discovering significant types of relations from the web is challenging because of its open nature.
In this paper we survey several important types of semantic relations. This paper also covers the relation extraction (RE) approaches which are divided into: supervised approach, which contains Feature base and Kernel base, and the unsupervised approach. Three relation extraction algorithms are discussed: Support Vector Machine (SVM), Genetic algorithm and Naive Bayes classifier
This survey would be useful for three kinds of readers First the Newcomers in the field who want to quickly learn about relation extraction. Second the researchers who want to know how the various relation extraction techniques developed over time. Third the trainers who just need to know which RE technique works best in different settings |
| first_indexed | 2024-12-14T20:58:41Z |
| format | Article |
| id | doaj.art-2660a0ebc4224cd38bdc22470d386a21 |
| institution | Directory Open Access Journal |
| issn | 1812-125X 2664-2530 |
| language | Arabic |
| last_indexed | 2024-12-14T20:58:41Z |
| publishDate | 2020-03-01 |
| publisher | College of Education for Pure Sciences |
| record_format | Article |
| series | مجلة التربية والعلم |
| spelling | doaj.art-2660a0ebc4224cd38bdc22470d386a212022-12-21T22:47:38ZaraCollege of Education for Pure Sciencesمجلة التربية والعلم1812-125X2664-25302020-03-0129125326510.33899/edusj.2020.164377164377A Survey Study on Relation Extraction for Web PagesGhada AlsaighGhayda Al-TalibAlaa Y. TaqaNatural language means a language that is used for communication by human. Natural Language Processing (NLP) helps machines to understand the natural language. The natural language for the web pages consists of many semantic relations between entities. Discovering significant types of relations from the web is challenging because of its open nature. In this paper we survey several important types of semantic relations. This paper also covers the relation extraction (RE) approaches which are divided into: supervised approach, which contains Feature base and Kernel base, and the unsupervised approach. Three relation extraction algorithms are discussed: Support Vector Machine (SVM), Genetic algorithm and Naive Bayes classifier This survey would be useful for three kinds of readers First the Newcomers in the field who want to quickly learn about relation extraction. Second the researchers who want to know how the various relation extraction techniques developed over time. Third the trainers who just need to know which RE technique works best in different settingshttps://edusj.mosuljournals.com/article_164377_8c74eecd5a44832b9889278c7d1872a3.pdfrelation extractionweb pagesnlp |
| spellingShingle | Ghada Alsaigh Ghayda Al-Talib Alaa Y. Taqa A Survey Study on Relation Extraction for Web Pages مجلة التربية والعلم relation extraction web pages nlp |
| title | A Survey Study on Relation Extraction for Web Pages |
| title_full | A Survey Study on Relation Extraction for Web Pages |
| title_fullStr | A Survey Study on Relation Extraction for Web Pages |
| title_full_unstemmed | A Survey Study on Relation Extraction for Web Pages |
| title_short | A Survey Study on Relation Extraction for Web Pages |
| title_sort | survey study on relation extraction for web pages |
| topic | relation extraction web pages nlp |
| url | https://edusj.mosuljournals.com/article_164377_8c74eecd5a44832b9889278c7d1872a3.pdf |
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