Aspect and Opinion Word Extraction on Opinion Sentences in Bahasa Indonesia using Rule Based Generated from Regular Expression

Abstract

Extracting aspects and opinion words is important in ABSA study. Generally, aspect extraction was conducted first then determining a pair of opinion words from the aspects. The process allows errors to occur. This study proposes an approach to obtain the appropriate pair of aspect and opinion words in opinion sentences using rule-based method generated from regular expressions. The strength of this process is that it enables to obtain a pair of aspects and opinion words simultaneously. Three methods are developed this approach (1) selection of aspect-based opinion sentences in user reviews, (2) extraction of candidate aspects and opinion words in aspect-based opinion sentences and (3) aspect categorization. This study enables to extract pairs of aspects and opinion words using rule-based aspects generated from regular expression. Determining valid aspects uses aspect extraction. Evaluation of aspect categorization shows the value of precision of 0.82, recall of 0.70 and f-measure of 0.75.