The DOI matches its Crossref record.
RevMiner: an extractive interface for navigating reviews on a smartphone
Abstract
Smartphones are convenient, but their small screens make searching, clicking, and reading awkward. Thus, perusing product reviews on a smartphone is difficult. In response, we introduce RevMiner - a novel smartphone interface that utilizes Natural Language Processing techniques to analyze and navigate reviews. RevMiner was run over 300K Yelp restaurant reviews extracting attribute-value pairs, where attributes represent restaurant attributes such as sushi and service, and values represent opinions about the attributes such as fresh or fast. These pairs were aggregated and used to: 1) answer queries such as "cheap Indian food", 2) concisely present information about each restaurant, and 3) identify similar restaurants. Our user studies demonstrate that on a smartphone, participants preferred RevMiner's interface to tag clouds and color bars, and that they preferred RevMiner's results to Yelp's, particularly for conjunctive queries (e.g., "great food and huge portions"). Demonstrations of RevMiner are available at revminer.com.
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Online reviews have been mentioned as a useful resource to assist BLV customers' desire for more product information.
“Online reviews have been mentioned as an useful resource to assist BLV customers' desire for more product information [16, 30, 31], such as supporting question-answering[20, 36] and generating summaries [12, 15].”
From Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users (2021) · cites this paper as [12]
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Wang, R., Chen, Z., Zhang, M. R., Li, Z., Liu, Z., Dang, Z., Yu, C., & Chen, X. '. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445547 · Cited by 42
Metadata
- Authors
- Huang, J., Etzioni, O., Zettlemoyer, L., Clark, K., & Lee, C.
- Affiliations
- University of Washington (US)
- Venue
- Proceedings of the 25th annual ACM symposium on User interface software and technology
- Publisher
- ACM
- Published
- 2012-10-07
- Pages
- 3-12
- OpenAlex
- W2150071643
- Cited by
- 37
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2022: 2 · 2021: 1 · 2020: 3 · 2019: 2 · 2018: 3 · 2017: 3 · 2016: 4 · 2015: 8 · 2014: 5 · 2013: 4
- FWCI
- 3.86
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion)
- Funders
- National Science Foundation
- University of Washington
- Fogarty International Center
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- smartphone interface, product reviews, restaurant reviews, Yelp, attribute-value pairs, sentiment analysis, conjunctive queries, query answering, user study
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