This disclosure relates generally to method and system for product data categorization based on text and attribute factorization. The method includes acquiring an input describing a set of product data from an application data store for categorization. The set of product data by removing extraneous text based on a predefined template. Further a dictionary for the set of product data based on a set of attributes comprising a product key with its corresponding product value. Further, a multi-level contextual data for the set of product data are extracted by assigning a weight to each product data based on likelihood and creating a set of datapoints for each product data. The set of product data are categorized by feeding the set of data points to a set of predefined parameters to compute a minimum count, a total size, total number of epochs, a skip gram value and a hierarchical softmax.