Identifying Persian Words’ Senses Automatically by Utilizing the Word Embedding Method

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.

GHAYOOMI MASOOD

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

Journal Paper

Paper Information

Journal: Iranian Journal of Information Processing & Management Year:2019 | Volume:35 | Issue:1 Page(s): 25-50

Download Full-Text

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

Persian Verion

View:

459

Download:

Cites:

Information Journal Paper

Title

Identifying Persian Words’ Senses Automatically by Utilizing the Word Embedding Method

Author(s)

GHAYOOMI MASOOD | Issue Writer Certificate

Keywords

Word EmbeddingQ1

ClusteringQ1

Unsupervised Machine LearningQ1

Vector SpaceQ1

Natural Language ProcessingQ1

Word sense representationQ1

PersianQ1

Abstract

A word is the smallest unit in a language that has ‘ form’ and ‘ meaning’ . The word might have more than one meaning in which its exact meaning is determined according to the context it is appeared. Collecting all words’ senses manually is a tedious and time consuming task. Moreover, it is possible that the words’ meanings change over time such that the meaning of an existing word will become unusable or a new meaning will be added to the word. Computational methods is one of the approaches used for identifying words’ senses with respect to the linguistic contexts. In this paper, we put an effort to propose an algorithm to identify senses of Persian words automatically without a human supervision. To reach this goal, we utilize the Word Embedding method in a Vector Space model. To build words’ vectors, we use an algorithm based on the neural network approach to gather the context information of the words in the vectors. In the proposed model of this research, the divisive Clustering algorithm as one of hierarchical Clustering algorithms fits with the requirements of our research question. In the proposed model, two modes, namely the Sentence-based and the Context-based, are introduced to identify words’ senses. In the Sentence-based mode, all of the words in a sentence that contain the target word are involved to build the sentence vector; while in the Context-based mode, only a limited number of surrounding words of the target word is involved to build the sentence vector. Two evaluation metrics, namely internal and external, are required to evaluate the performance of the Clustering algorithm. The silhouette score for each cluster is computed as the internal evaluation metric for both modes of the proposed model. The external evaluation requires a gold standard data for which a data set containing 20 ambiguous words and 100 sentences for each target word is developed. According to the obtained results of the internal evaluation, the Sentence-based mode has higher density of clusters than the Contextbased mode, and the difference between them is statistically significant. According to the V-and F-measure evaluation metrics in the external evaluation, the Contextbased mode has obtained higher performance against the baselines with statistically significant difference.

Cites

No record.

References

No record.

Cite

APA: Copy

GHAYOOMI, MASOOD. (2019). Identifying Persian Words’ Senses Automatically by Utilizing the Word Embedding Method. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), 35(1 ), 25-50. SID. https://sid.ir/paper/131059/en

Vancouver: Copy

GHAYOOMI MASOOD. Identifying Persian Words’ Senses Automatically by Utilizing the Word Embedding Method. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY)[Internet]. 2019;35(1 ):25-50. Available from: https://sid.ir/paper/131059/en

IEEE: Copy

MASOOD GHAYOOMI, “Identifying Persian Words’ Senses Automatically by Utilizing the Word Embedding Method,” IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), vol. 35, no. 1 , pp. 25–50, 2019, [Online]. Available: https://sid.ir/paper/131059/en

Related Journal Papers