Multi Aspect Sentiment of Beauty Product Reviews using SVM and Semantic Similarity

IRBAH SALSABILA

Informasi Dasar

52 kali
21.04.4814
005.1
Karya Ilmiah - Skripsi (S1) - Reference

Beauty products are an important requirement for people, especially women. But, not all beauty products give the expected results. A review in the form of opinion can help the consumers to know the overview of the product. The reviews were analyzed using a multi-aspect-based approach to determine the aspects of the beauty category based on the reviews written on femaledaily.com. First, the review goes through the preprocessing stage to make it easier to be processed, and then it used the Support Vector Machine (SVM) method with the addition of Semantic Similarity and TF-IDF weighting. From the test result using semantic, get an accuracy of 93% on the price aspect, 92% on the packaging aspect, and 86% on the scent aspect.

Subjek

COMPUTER PROGRAMS
 

Katalog

Multi Aspect Sentiment of Beauty Product Reviews using SVM and Semantic Similarity
 
 
Indonesia

Sirkulasi

Rp. 0
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Tidak

Pengarang

IRBAH SALSABILA
Perorangan
Yuliant Sibaroni
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2021

Koleksi

Kompetensi

 

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