TY - CPAPER SN - 978-1-4503-2038-2 AU - Gindl, Stefan AU - Weichselbraun, Albert AU - Scharl, Arno T1 - Rule-based opinion target and aspect extraction to acquire affective knowledge T2 - WWW '13 Companion. Proceedings of the 22nd International Conference on World Wide Web ED - Schwabe, Daniel ED - Almeida, Virgílio ED - Glaser, Hartmut ED - Baeza-Yates, Ricardo ED - Moon, Sue PY - 2013 CY - New York, NY, USA PB - Association for Computing Machinery (ACM) UR - https://doi.org/10.1145/2487788.2487994 SP - 557 EP - 563 AB - 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. TS - CrossRef Y3 - 21.05.2021 C7 - WWW'13 C1 - Rio de Janeiro, Brazil, 13.-17. Mai AD - PUC-Rio - Brazil UFMG - Brazil CGI.br - Brazil Yahoo! Labs - Spain & Chile KAIST - South Korea MODUL University Vienna, Vienna, Austria University of Applied Sciences Chur, Chur, Switzerland M4 - Citavi ER -