Persian Opinion Mining based on Transfer Learning

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Dehghani Ashkezari Saeed; DERHAMI VALI; ZAREH BIDOKI ALI MOHAMMAD; Basiri Mohammad Ehsan

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Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2020 | Volume:50 | Issue:3 (93) Page(s): 1215-1224

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Information Journal Paper

Title

Persian Opinion Mining based on Transfer Learning

Author(s)

Dehghani Ashkezari Saeed | DERHAMI VALI | ZAREH BIDOKI ALI MOHAMMAD | Basiri Mohammad Ehsan | Issue Writer Certificate

Keywords

Opinion mining

Transfer learning

Feature transfer

Polarity

Abstract

In the past decade, the study of human opinions, feelings and tendencies has been very effective in the decision-making of managers and individuals. Machine learning algorithms play an important role in the field of Opinion mining, but they suffer from a big problem: most of the machine learning algorithms assume that the feature dimensions and data distribution are equal, but most of real-world applications don't follow these assumptions. In fact, the data that the algorithm will receive in the future may have different dimensions or distributions. In this article, a new method for improving sentiment analysis of opinions is proposed by the aid of featurebased Transfer learning. In the proposed method, initially, the feature or topic of the opinion in the source language domain is identified. Then, by collecting adjectives, adverbs and totally a package of probabilities about that feature and by translating it into the target language, learning from the source language is transferred into the target language. An analysis of the proposed method on the data available at the Amazon store as the source domain indicates that by creating a pattern of Feature transferring in English, the Polarity of 77% of the opinions in Persian (recorded at the Digikala store) can be extracted that outperforms the SCL, SFA and TCA models with 9, 5 and 5 percent respectively.

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APA: Copy

Dehghani Ashkezari, Saeed, DERHAMI, VALI, ZAREH BIDOKI, ALI MOHAMMAD, & Basiri, Mohammad Ehsan. (2020). Persian Opinion Mining based on Transfer Learning. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 50(3 (93) ), 1215-1224. SID. https://sid.ir/paper/963543/en

Vancouver: Copy

Dehghani Ashkezari Saeed, DERHAMI VALI, ZAREH BIDOKI ALI MOHAMMAD, Basiri Mohammad Ehsan. Persian Opinion Mining based on Transfer Learning. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2020;50(3 (93) ):1215-1224. Available from: https://sid.ir/paper/963543/en

IEEE: Copy

Saeed Dehghani Ashkezari, VALI DERHAMI, ALI MOHAMMAD ZAREH BIDOKI, and Mohammad Ehsan Basiri, “Persian Opinion Mining based on Transfer Learning,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 50, no. 3 (93) , pp. 1215–1224, 2020, [Online]. Available: https://sid.ir/paper/963543/en

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