Warehousing and Analyzing Massive RFID Data Sets

By Hector Gonzalez, Jiawei Han, Xiaolei Li, Diego Klabjan. IEEE International Conference on Data Engineering, 2006

303 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/07ca97a33f7e3454868373884a1f6ce6a4944b2b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Amit P. Sheth
2. Eleonora Borgia
3. Lalit Chettri
4. Rabindranath Bera

In Information Systems

1. Amit P. Sheth
2. Payam M. Barnaghi
3. Eleonora Borgia

In Signal Processing

1. Amit P. Sheth
2. Eleonora Borgia

Citations in the corpus

• The Internet of Things: A Survey from the Data-Centric Perspective (2013, unknown): “The work in [42] proposes methods for reducing this redundancy.”
• The Internet of Things vision: Key features, applications and open issues (2014, methodology): “For example, the RFID-Cuboids model [211] manages efficiently massive RFID data, achieving a significant data compression and speeding up the analysis process.”
• Machine learning for Internet of Things data analysis: A survey (2017, background): “[10] performed research into warehousing Radio Frequency Identification (RFID) data, with a focus specifically on managing and mining RFID stream data.”