Open AccessNews recommendation system using machine learning
Author(s) -
Neha Rani,
Sudhir Pathak
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.27.11748
Subject(s) - support vector machine , artificial neural network , artificial intelligence , stock market , computer science , machine learning , classifier (uml) , stock (firearms) , data mining , geography , context (archaeology) , archaeology
The forecasting of financial news is yet becoming the main issue to divide the new into different classes on the basis of present time series. Moreover, it might be utilized for predicting and analyzing the stock market for the particular industry. Thus, the new content is significantly important to influence market forecast report. In this paper, the financial news from four countries namely America, Australia, India and South Africa along with their stop words are consider. The words along with their weighted values are determined and then the neural network is trained. Here, artificial neural network is used for classifying the appropriate results for the given input data. At last the comparison of ANN with SVM is shown. Experiments show that the ANN classification provides high accuracy to predict the news than the SVM classifier.