A Parallel Computing Method for Entity Recognition based on MapReduce

Yushui Geng, Peng Li, Jing Zhao
2016 Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)   unpublished
With the rapid development of industrial automation, there are huge amounts of duplicate data refer to the same entity in the data sets have brought enormous challenges in data analysis. To accommodate the entity recognition of huge amounts of data, this paper presents a parallel computing method for entity recognition based on MapReduce. Through the detailed introduction to the MapReduce framework, running the applications on the Hadoop platform and parallel processing data sets to recognize
more » ... sets to recognize the data entities. The experiments show that the proposed method greatly enhanced the recognition speed and accuracy, which has better effectiveness to meet the demand for entity recognition than other methods.
doi:10.2991/icence-16.2016.122 fatcat:gr6432w42jh6diwagqcfzkhnfi