Paper Info
Title
Rule-based opinion target and aspect extraction to acquire affective knowledge
Abstract
Opinion holder and opinion target extraction are among the most popular and challenging problems tackled by opinion mining researchers, recognizing the significant business value of such components and their importance for applications such as media monitoring and Web intelligence. This paper describes an approach that combines opinion target extraction with aspect extraction using syntactic patterns. It expands previous work limited by sentence boundaries and includes a heuristic for anaphora resolution to identify targets across sentences. Furthermore, it demonstrates the application of concepts known from research on open information extraction to the identification of relevant opinion aspects. Qualitative analyses performed on a corpus of 100,000 Amazon product reviews show that the approach is promising. The extracted opinion targets and aspects are useful for enriching common knowledge resources and opinion mining ontologies, and support practitioners and researchers to identify opinions in document collections.
Year
DOI
Venue
2013
10.1145/2487788.2487994
WWW (Companion Volume)
Keywords
Field
DocType
opinion target,opinion mining ontology,relevant opinion aspect,opinion target extraction,open information extraction,amazon product review,affective knowledge,rule-based opinion target,aspect extraction,opinion mining researcher,web intelligence,opinion holder,opinion mining
Ontology (information science),Data science,Data mining,Rule-based system,World Wide Web,Business value,Web intelligence,Computer science,Sentiment analysis,Common knowledge,Information extraction,Media monitoring
Conference
ISBN
Citations 
PageRank 
978-1-4503-2038-2
8
0.52
References 
Authors
16
3
Name
Order
Citations
PageRank
Stefan Gindl11529.93
Albert Weichselbraun229128.39
Arno Scharl369667.13