Automatic Synset Extraction from Text Documents Using a Graph-Based Clustering Approach via Maximal Cliques Finding

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Khorasani Mahsa; MINAEI BIDGOLI BEHROUZ; Saedi Chakaveh

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH Year:2019 | Volume:11 | Issue:1 Page(s): 27-35

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Information Journal Paper

Title

Automatic Synset Extraction from Text Documents Using a Graph-Based Clustering Approach via Maximal Cliques Finding

Author(s)

Khorasani Mahsa | MINAEI BIDGOLI BEHROUZ | Saedi Chakaveh | Issue Writer Certificate

Keywords

Automatic Synset Extraction

Semantic Relation

Graph-based Clustering

CBC clustering

Persian

Abstract

Semantic Relations between words like synsets are used in automatic ontology production which is a strong tool in many NLP tasks. Synset extraction is usually dependent on other languages and resources using techniques such as mapping or translation. In our proposed method, synsets are extracted merely from text and corpora. This frees us from the need for special resources including Word-Nets or dictionaries. The representation model for words of corpus is based on Vector Space model and the most similar words to each are extracted based on common features count (CFC) using a modified cosine similarity measure. Furthermore, a graph-based soft clustering approach is applied to create clusters of synonymous words. To examine performance of the proposed method, Extracted synsets were compared to other Persian semantic resources. Results show an accuracy of 80. 25%, which indicates improvement in comparison to the 69. 5% accuracy of pure clustering by committee method.

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APA: Copy

Khorasani, Mahsa, MINAEI BIDGOLI, BEHROUZ, & Saedi, Chakaveh. (2019). Automatic Synset Extraction from Text Documents Using a Graph-Based Clustering Approach via Maximal Cliques Finding. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, 11(1), 27-35. SID. https://sid.ir/paper/763422/en

Vancouver: Copy

Khorasani Mahsa, MINAEI BIDGOLI BEHROUZ, Saedi Chakaveh. Automatic Synset Extraction from Text Documents Using a Graph-Based Clustering Approach via Maximal Cliques Finding. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH[Internet]. 2019;11(1):27-35. Available from: https://sid.ir/paper/763422/en

IEEE: Copy

Mahsa Khorasani, BEHROUZ MINAEI BIDGOLI, and Chakaveh Saedi, “Automatic Synset Extraction from Text Documents Using a Graph-Based Clustering Approach via Maximal Cliques Finding,” INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, vol. 11, no. 1, pp. 27–35, 2019, [Online]. Available: https://sid.ir/paper/763422/en

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