Parallel Text Categorization of Massive Text Based on Hadoop
Xiaojun Xiang, Yang Gao, Lin Shang, Yang Yu-bin · 2011
In recent years,there have been extensive studies and rapid progresses in automatic text categorization,which is one of the hotspots and key techniques in the information retrieval and data mining field.In recent years,as the text data grows exponentially,to effectively manage the large storage of data,we must use efficient algorithm to process it in the distributed environment.In this paper,we implemented a simple and effective text categorization algorithm on hadoop——TFIDF classifier,an algorithm based on vector space model,cosine similarity was applied as the metrics.The experiments on two datasets show that the parallel algorithm is effective on large storage of data and can be applied in practical application field.