MapReduce based named entity recognition for biology literature

With the rapid development of biology, its relevant literature will be more and more important for researchers to dig out more valuable knowledge. Named Entity Recognition (NER) for biology literature is a very common and important task in these works. With the increase of the literature amount, the recognition speed becomes slower and less accurate. In order to tackle this problem, a MapReduce based NER is used to reduce the running time by leveraging parallel processing. Experimental results show that the application of entity naming recognition to the MapReduce framework has greatly improved in the CRF model training process and entity recognition process. Name entity recognition is accommodated to parallel framework to solve recognition problem rapidly and accurately.