The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Addressing Complex and Subjective Product-Related Queries with Customer Reviews
Open accessAbstract
Online reviews are often our first port of call when considering products and purchases online. When evaluating a potential purchase, we may have a specific query in mind, e.g. `will this baby seat fit in the overhead compartment of a 747?' or `will I like this album if I liked Taylor Swift's 1989?'. To answer such questions we must either wade through huge volumes of consumer reviews hoping to find one that is relevant, or otherwise pose our question directly to the community via a Q/A system.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
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 [20]
Citations
Cites
Separating Style and Content with Bilinear Models
Tenenbaum, J. B., & Freeman, W. T. (2000) · Neural Computation · doi:10.1162/089976600300015349 · Cited by 840 · cited 1×
“Bilinear models [8, 12, 42] can help to address this issue by learning complex mappings between words in one corpus and words in another (or more generally between arbitrary feature spaces).”
Background
Flagged first, then by citations
Research works printed but not linked: 45
- 10.1145/1341531.1341557 · DOI
- 10.1145/2339530.2339665 · DOI
- 10.1145/345508.345576 · DOI
- 10.1145/1526709.1526717 · DOI
- 10.1145/1401890.1401994 · DOI
- Carenini G., 2006, ACL
- 10.5555/1613715.1613757 · DOI
- 10.1145/1526709.1526802 · DOI
- 10.1145/1526709.1526729 · DOI
- 10.5555/1622487.1622501 · DOI
- Ferrucci D., 2010, Building Watson: An overview of the DeepQA project. In AI Magazine
- Freeman W., 1996, CVPR
- Gangadharaiah R., 2013, International Joint Conference on Natural Language Processing
- Ganu G., 2009, WebDB
- 10.1145/1148170.1148211 · DOI
- He J., 2011, JMLR
- 10.1145/1014052.1014073 · DOI · Paper page
- 10.1162/neco.1991.3.1.79 · DOI · Paper page
- 10.1145/1099554.1099572 · DOI
- 10.1016/S0306-4573(00)00015-7 · DOI
- 10.1145/1321440.1321575 · DOI
- 10.3115/1667583.1667617 · DOI
- Kumar A., 2015, Ask me anything: Dynamic memory networks for natural language processing. CoRR, abs/1506.07285 · arXiv
- Li J., 2007, NIST
- 10.3115/1073083.1073160 · DOI
- 10.1145/2063576.2063584 · DOI
- Manning C., 2009, An Introduction to Information Retrieval
- 10.1145/2507157.2507163 · DOI
- 10.1145/2783258.2783381 · DOI · Paper page
- 10.1145/215206.215334 · DOI
- 10.5555/1667583.1667637 · DOI
- Moschitti A., 2007, ACL
- Nazi A., 2015, ICWSM
- 10.1145/1935826.1935843 · DOI
- 10.5555/2021855.2021876 · DOI
- 10.1145/2766462.2767748 · DOI
- 10.1145/290941.291008 · DOI · Paper page
- 10.1109/ICDM.2010.127 · DOI · Paper page
- Rendle S., 2009, UAI
- 10.1145/2187980.2188202 · DOI
- 10.1145/2766462.2767738 · DOI
- 10.1145/1835804.1835903 · DOI
- Lin C., 2004, ACL Workshop on Text Summarization Branches Out
- 10.3115/1119355.1119372 · DOI
- 10.1145/2661829.2661908 · DOI
Cited by
Sorted by citations
Mulla, N., & Gharpure, P. (2023) · Progress in Artificial Intelligence · doi:10.1007/s13748-023-00295-9 · Cited by 132
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
- McAuley, J., & Yang, A.
- Affiliations
- University of California San Diego (US)
- ORCID
- McAuley, Julian
- Venue
- Proceedings of the 25th International Conference on World Wide Web
- Published
- 2016-04-11
- Pages
- 625-635
- OpenAlex
- W2243869100
- Cited by
- 190
- References
- 1
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 16 · 2023: 17 · 2022: 20 · 2021: 16 · 2020: 29 · 2019: 32 · 2018: 36 · 2017: 9 · 2016: 4
- FWCI
- 14.55
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International World Wide Web Conference (WWW) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
- Keywords
- customer reviews, query answering, online reviews, product recommendation, Q&A system
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
