International Journal of Engineering and Technology

Multilabel classification is the problem of assigning a set of positive labels to an instance and recently it is highly required in applications like protein function classification, music categorization, gene classification and document classification for easy identification and retrieving of information. Labeling the documents of the web manually is a time consuming and a difficult task due to the size of the web which is a huge information resource and to overcome this difficulty, we propose an algorithm of MapReduce for classifying labels to the documents of the web. MapReduce is a framework of parallel programming model with the functions map and reduce and meets a number of varieties of applications. In our approach, the documents of the web are given to the MapReduce framework and the MapReduce framework assigns the set of positive labels to the documents of the web using binary classification of binary classifier. On experimentation, our proposed approach satisfactorily classifies the labels to the documents of the web.