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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
5098
Venue
SIGMOD
Year
2016
Pagerank
5.6609383e-05
Overall Rank
5,152 | 64.16%
DOI
10.1145/2882903.2882907

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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
74 Efficient Query Evaluation on Probabilistic Databases 2004 VLDB 0.00057857292
1,594 Adaptive Cleaning for RFID Data Streams 2006 VLDB 0.00011222484
2,070 Temporal Management of RFID Data 2005 VLDB 9.6254139e-05
2,466 Managing RFID Data 2004 VLDB 8.7505796e-05
5,808 Leveraging Spatio-Temporal Redundancy for RFID Data Cleansing 2010 SIGMOD 5.3185608e-05
6,199 Supporting RFID-based Item Tracking Applications in Oracle DBMS Using a Bitmap Datatype 2005 VLDB 5.1605194e-05
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