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DocRicher: An Automatic Annotation System for Text Documents Using Social Media

Summary: DocRicher automatically annotates documents by breaking text into topical passages and querying social media for annotations. Four components: text analysis, query construction, data assignment, and user feedback; data fusion merges multi-context results and supports rating or manual annotation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5056
Venue
SIGMOD
Year
2015
Pagerank
5.093636e-05
Overall Rank
12,114 | 16.89%
DOI
10.1145/2723372.2735379

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Authors

BibTeX Citation

@inproceedings{hu_sigmod15,
        title = {{DocRicher: An Automatic Annotation System for Text Documents Using Social Media}},
        author = {Hu, Qiang and Liu, Qi and Wang, Xiaoli and Tung, Anthony K.H. and Goyal, Shubham and Yang, Jisong},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2735379},
        url = {https://dl.acm.org/doi/10.1145/2723372.2735379},
        year = {2015}
}

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