Improved literature recommendation system through the fusion mode of conformity bias elimination and keyword preference
Integrity signals
Registry
Cites
Statistics
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?
Conformity bias is frequently observed in users' ratings and reviews.
“This bias is frequently observed in users' ratings [62, 63] and reviews [26].”
From A Deep Dive into Fairness, Bias, Threats, and Privacy in Recommender Systems: Insights and Future Research (2024) · cites this paper as [63]
Cites
Disentangling User Interest and Conformity for Recommendation with Causal Embedding
Zheng, Y., Gao, C., Li, X., He, X., Li, Y., & Jin, D. (2021) · Proceedings of the Web Conference 2021 · doi:10.1145/3442381.3449788 · Cited by 356 · see citing works
Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation
Zhao, Z., Chen, J., Zhou, S., He, X., Cao, X., Zhang, F., & Wu, W. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2022.3218994 · Cited by 117 · see citing works
Recent Trends in Academic Journal Growth
Gu, X., & Blackmore, K. L. (2016) · Scientometrics · doi:10.1007/s11192-016-1985-3 · Cited by 77 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Roy, F., Ding, X., Choo, K. K. R., & Zhou, P. (2024) · arXiv · doi:10.48550/arxiv.2409.12651
- Authors
- Pan, Q., Li, S., Zheng, T., Ma, F., & Huang, J.
- Affiliations
- Nanjing University of Finance and Economics (CN)
- Corresponding author
- Li, Shuqing
- Zheng, Tiansheng
- ORCID
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2024-08
- Volume
- 247
- Pages
- 123227
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W4391057910
- Cited by
- 7
- References
- 3
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 2
- FWCI
- 2.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Expert Systems with Applications (publishedVersion)
- Funders
- Key Research and Development Program of Jiangxi Province
- National Natural Science Foundation of China (61973151)
- Chinese Academy of Engineering
- Chinese Academy of Sciences
- Jiangsu Province Department of Science and Technology (BE2021001-4)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Keywords
- literature recommendation, conformity bias, keyword selection, data fusion, user access behavior
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.
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