TY - GEN
T1 - Multi-facets quality assessment of online opinionated expressions
AU - Lau, Raymond Y.K.
AU - Zhang, Wenping
AU - Xia, Yunqing
AU - Song, Dawei
PY - 2011
Y1 - 2011
N2 - In the Web 2.0 era, there has been an explosive growth of user-contributed data on the Web. Among the user-contributed data, the sheer volume of online reviews (or comments) provide enterprise with invaluable market intelligence about potential customers' preferences for various products and services. However, there has been growing concerns about the quality of these uncontrolled user-contributed online reviews. Despite numerous research work has been conducted on opinion mining and opinion retrieval, little work has been done to develop effective quality metrics to assess the quality of opinionated expressions. To discover rich and accurate business intelligence from online opinionated expressions, an objective quality-based filtering process is essential for any opinion mining systems. The main contribution of this paper is the design, development, and evaluation of a novel multi-facet quality metric for the assessment of the informativeness of opinionated expressions such as online product reviews. Our preliminary experiments show that the proposed multi-facets quality metric is more effective than a quality assessment approach constructed based on user-generated helpful votes.
AB - In the Web 2.0 era, there has been an explosive growth of user-contributed data on the Web. Among the user-contributed data, the sheer volume of online reviews (or comments) provide enterprise with invaluable market intelligence about potential customers' preferences for various products and services. However, there has been growing concerns about the quality of these uncontrolled user-contributed online reviews. Despite numerous research work has been conducted on opinion mining and opinion retrieval, little work has been done to develop effective quality metrics to assess the quality of opinionated expressions. To discover rich and accurate business intelligence from online opinionated expressions, an objective quality-based filtering process is essential for any opinion mining systems. The main contribution of this paper is the design, development, and evaluation of a novel multi-facet quality metric for the assessment of the informativeness of opinionated expressions such as online product reviews. Our preliminary experiments show that the proposed multi-facets quality metric is more effective than a quality assessment approach constructed based on user-generated helpful votes.
UR - https://www.scopus.com/pages/publications/80053447686
U2 - 10.1007/978-3-642-24396-7_17
DO - 10.1007/978-3-642-24396-7_17
M3 - Conference contribution
AN - SCOPUS:80053447686
SN - 9783642243950
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 212
EP - 225
BT - Web Information Systems Engineering - WISE 2010 Workshops - WISE 2010 International Symposium WISS and International Workshops CISE, MBC, Revised Selected Papers
PB - Springer Verlag
T2 - Workshops on Web Information Systems Engineering, WISE 2010: 1st International Symposium on Web Intelligent Systems and Services, WISS 2010, 2nd International Workshop on Mobile Business Collaboration, MBC 2010 and 1st International Workshop on Cloud Information System Engineering, CISE 2010
Y2 - 12 December 2010 through 14 December 2010
ER -