Automatic Keyword Extraction from Persian short Text Using word2vec

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Hajipoor O.; SADIDPOUR S.S.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF ELECTRONIC AND CYBER DEFENCE Year:2020 | Volume:8 | Issue:2 (30) Page(s): 105-114

Download Full-Text

Persian Verion

View:

978

Download:

Cites:

Information Journal Paper

Title

Automatic Keyword Extraction from Persian short Text Using word2vec

Author(s)

Hajipoor O. | SADIDPOUR S.S. | Issue Writer Certificate

Keywords

Keyword ExtractionQ1

Persian LanguageQ1

Text MiningQ1

Word SimilarityQ1

Word2vecQ1

Abstract

With the growing number of Persian electronic documents and texts, the use of quick and inexpensive methods to access desired texts from the extensive collection of these documents becomes more important. One of the effective techniques to achieve this goal is the extraction of the keywords which represent the main concept of the text. For this purpose, the frequency of a word in the text can not be a proper indication of its significance and its crucial role. Also, most of the Keyword Extraction methods ignore the concept and semantic of the text. On the other hand, the unstructured nature of new texts in news and electronic documents makes it difficult to extract these words. In this paper, an automated, unsupervised method for keywords extraction in the Persian Language that does not have a proper structure is proposed. This method not only takes into account the probability of occurrence of a word and its frequency in the text, but it also understands the concept and semantic of the text by learning Word2vec model on the text. In the proposed method, which is a combination of statistical and machine learning methods, after learning Word2vec on the text, the words that have the smallest distance with other words are extracted. Then, a statistical equation is proposed to calculate the score of each extracted word using co-occurence and frequency. Finally, words which have the highest scores are selected as the keywords. The evaluations indicate that the efficiency of the method by the F-measure is 53. 92% which is 11% superior to other methods.

Cites

No record.

References

No record.

Cite

APA: Copy

Hajipoor, O., & SADIDPOUR, S.S.. (2020). Automatic Keyword Extraction from Persian short Text Using word2vec. JOURNAL OF ELECTRONIC AND CYBER DEFENCE, 8(2 (30) ), 105-114. SID. https://sid.ir/paper/387111/en

Vancouver: Copy

Hajipoor O., SADIDPOUR S.S.. Automatic Keyword Extraction from Persian short Text Using word2vec. JOURNAL OF ELECTRONIC AND CYBER DEFENCE[Internet]. 2020;8(2 (30) ):105-114. Available from: https://sid.ir/paper/387111/en

IEEE: Copy

O. Hajipoor, and S.S. SADIDPOUR, “Automatic Keyword Extraction from Persian short Text Using word2vec,” JOURNAL OF ELECTRONIC AND CYBER DEFENCE, vol. 8, no. 2 (30) , pp. 105–114, 2020, [Online]. Available: https://sid.ir/paper/387111/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops