Data Cleaning publication categorizer

RFID holds the promise of real-time identify-
ing, locating, tracking and monitoring phys-
ical objects without line of sight, and can
be used for a wide range of pervasive com-
puting applications. To achieve these goals,
RFID data has to be collected, filtered, and
transformed into semantic application data.
RFID data, however, contains false readings
and duplicates. Such data cannot be used
directly by applications unless they are fil-
tered and cleaned. While RFID data often
arrives quickly and is in high volume, its de-
tection usually demands efficient processing,
especially for those real-time monitoring ap-
plications. Meanwhile, the order preservation
of RFID tag observations are critical for many
applications. In this paper, we propose several
effective methods to filter RFID data, includ-
ing both noise removal and duplicate elimi-
nation. Our performance study demonstrates
the efficiency of our methods.