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Learning-Based Cleansing for Indoor RFID Data

Summary: Proposes IR-MHMM, a learning-based cleansing model for indoor RFID data that handles noise and missing readings without spatio-temporal prior knowledge. Learned from raw data with three IR-MHMM designs; achieves cleansing accuracy comparable to KB-heavy approaches. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5160
Venue
SIGMOD
Year
2016
Pagerank
6.3954412e-05
Overall Rank
5,030 | 65.50%
DOI
10.1145/2882903.2882907

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{baba_sigmod16,
        title = {{Learning-Based Cleansing for Indoor RFID Data}},
        author = {Baba, Asif Iqbal and Jaeger, Manfred and Lu, Hua and Pedersen, Torben Bach and Ku, Wei-Shinn and Xie, Xike},
        series = {{SIGMOD} '16},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2882903.2882907},
        url = {https://dl.acm.org/doi/10.1145/2882903.2882907},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
50 Efficient Query Evaluation on Probabilistic Databases 2004 VLDB 0.00043596705
1,331 Adaptive Cleaning for RFID Data Streams 2006 VLDB 0.00011130651
1,990 Temporal Management of RFID Data 2005 VLDB 9.3484709e-05
2,750 Managing RFID Data (Extended Abstract) 2004 VLDB 8.1650184e-05
5,834 Leveraging Spatio-Temporal Redundancy for RFID Data Cleansing 2010 SIGMOD 6.0721842e-05
6,152 Supporting RFID-based Item Tracking Applications in Oracle DBMS Using a Bitmap Datatype 2005 VLDB 5.9573045e-05
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