A Review of Unsupervised Approaches of Opinion Target Extraction from Unstructured Reviews

Khairullah Khan ； Baharum Baharudin ； Aurangzeb Khan Cis Department ； University Technology Petronas ； Malaysia

《Research Journal of Applied Sciences, Engineering and Technology》 7卷12期 (2014/03) Pp. 2400-2410

並列摘要

Opinion targets identification is an important task of the opinion mining problem. Several approaches have been employed for this task, which can be broadly divided into two major categories: supervised and unsupervised. The supervised approaches require training data, which need manual work and are mostly domain dependent. The unsupervised technique is most popularly used due to its two main advantages: domain independent and no need for training data. This study presents a review of the state of the art unsupervised approaches for opinion target identification due to its potential applications in opinion mining from web documents. This study compares the existing approaches that might be helpful in the future research work of opinion mining and features extraction.

並列關鍵字

Features extraction ； machine learning ； opinion mining ； opinion targets ； sentiment analysis