| Evaluating brand value on the web |
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International World Wide Web Conference
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Proceedings of the 3rd workshop on Information credibility on the web
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Madrid, Spain
SESSION: Vendor and product reputation
table of contents
Pages 67-74
Year of Publication: 2009
ISBN:978-1-60558-488-1
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Downloads (6 Weeks): 18, Downloads (12 Months): 82, Citation Count: 0
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ABSTRACT
The value of a brand name is an important factor that consumers often take into consideration when making their purchasing decisions. However, it is difficult for users to evaluate correctly the value of a brand name, especially when they encounter it for the first time. In reality, sometimes a brand's description or its use is purposely manipulated so as to give an impression of high value. In another way, a non-existing brand name may be used to attract consumers. We call such names "glorified terms." In this paper, we propose a method for evaluating a brand's value from texts on the Web. To this end, we first acquire candidates of attributes useful for evaluating whether a term is a brand name or a glorified term. The candidates are evaluated according to the idea whereby explanations about a real brand name often contain attributes describing its quality. We implemented a prototype system especially for agricultural and livestock products. The system judges whether a given one is a glorified term or a well-known brand name from several viewpoints. We conducted preliminary experiments and we achieved 74% - 85% accuracy rate.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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D. G. Goldstein and G. Gigerenzer. The recognition heuristic: How ignorance makes us smart. in G. Gigerenzer, P.M. Todd, and the ABC Research Group, Simple Heuristics that make Us Smart, pages 37--58, 1999.
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3
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Nan Hu , Paul A. Pavlou , Jennifer Zhang, Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication, Proceedings of the 7th ACM conference on Electronic commerce, p.324-330, June 11-15, 2006, Ann Arbor, Michigan, USA
[doi> 10.1145/1134707.1134743]
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4
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5
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6
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Fotis Kokkoras , Efstratia Lampridou , Konstantinos Ntonas , Ioannis Vlahavas, MOpiS: A Multiple Opinion Summarizer, Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications, October 02-04, 2008, Syros, Greece
[doi> 10.1007/978-3-540-87881-0_11]
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7
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8
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H. Ohshima, S. Oyama, and K. Tanaka. Searching coordinate terms with their context from the web. In K. Aberer, Z. Peng, E. A. Rundensteiner, Y. Zhang, and X. Li, editors, WISE, volume 4255 of Lecture Notes in Computer Science, pages 40--47. Springer, 2006.
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9
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H. Ohshima and K. Tanaka. High-speed extraction of related terms by bi-directional syntax patterns from web search engines. DBSJ Journal, 7(3):1--6, December 2008 (in Japanese).
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10
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Y. Suzuki, H. Takamura, and M. Okumura. Application of semi-supervised learning to evaluative expression classification. In Proceedings of CICLing-06, the 7th international conference on Computational Linguistics and Intelligent Text Processing, pages 502--513, Mexico City, MX, 2006.
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