TY - GEN
T1 - Genetic algorithm based correlation enhanced prediction of online news popularity
AU - Choudhary, Swati
AU - Sandhu, Angkirat Singh
AU - Pradhan, Tribikram
PY - 2017
Y1 - 2017
N2 - Online News is an article which is meant for spreading awareness of any topic or subject published on the Internet and is available to a large section of users to gather information. For complete knowledge proliferation we need to know the right way and time to do so. For achieving this goal we have come up with a model which on the basis of, multiple factors, like describing the article type (structure and design) and publishing time predicts popularity of the article. In this paper we use Correlation techniques to get the dependency of the popularity obtained from an article, and then we use Genetic Algorithm to get the optimum attributes or best set which should be considered while formatting the article. Data has been procured from UCI Machine Learning Repository with 39644 articles with sixty condition attributes and one decision attribute. We implemented twelve different data learning algorithms on the above mentioned data set, including Correlation Analysis and Neural Network. We have also given a comparison of the performances got from various algorithms in the Result section.
AB - Online News is an article which is meant for spreading awareness of any topic or subject published on the Internet and is available to a large section of users to gather information. For complete knowledge proliferation we need to know the right way and time to do so. For achieving this goal we have come up with a model which on the basis of, multiple factors, like describing the article type (structure and design) and publishing time predicts popularity of the article. In this paper we use Correlation techniques to get the dependency of the popularity obtained from an article, and then we use Genetic Algorithm to get the optimum attributes or best set which should be considered while formatting the article. Data has been procured from UCI Machine Learning Repository with 39644 articles with sixty condition attributes and one decision attribute. We implemented twelve different data learning algorithms on the above mentioned data set, including Correlation Analysis and Neural Network. We have also given a comparison of the performances got from various algorithms in the Result section.
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U2 - 10.1007/978-981-10-3874-7_13
DO - 10.1007/978-981-10-3874-7_13
M3 - Conference contribution
AN - SCOPUS:85019757994
SN - 9789811038730
VL - 556
T3 - Advances in Intelligent Systems and Computing
SP - 133
EP - 144
BT - Computational Intelligence in Data Mining - Proceedings of the International Conference on CIDM
PB - Springer Verlag
T2 - 3rd International Conference on Computational Intelligence in Data Mining, ICCIDM 2016
Y2 - 10 December 2016 through 11 December 2016
ER -