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Fusing Data with Correlations

Summary: Models correlations among sources beyond simple copying (positive/negative, cross-domain, extractor rules) to improve truth discovery in web-harvested data. Evaluated on three real/synthetic datasets, it outperforms state-of-the-art methods by robustly fusing noisy, conflicting web data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4866
Venue
SIGMOD
Year
2014
Pagerank
0.00011384191
Overall Rank
1,273 | 91.27%
DOI
10.1145/2588555.2593764

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{pochampally_sigmod14,
        title = {{Fusing Data with Correlations}},
        author = {Pochampally, Ravali and Sarma, Anish Das and Dong, Xin Luna and Meliou, Alexandra and Srivastava, Divesh},
        series = {{SIGMOD} '14},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2588555.2593764},
        url = {https://dl.acm.org/doi/10.1145/2588555.2593764},
        year = {2014}
}

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