Abstract
The objective of this work is to propose a real time newsfeed system for an Android smart phone. This work proposes a system for automatic categorization of news items into a standard set of categories. Newsfeed system i.e. ‘INSIDER’ changes the things around a little. This android application is useful to provide relevant and up to date information as per user’s requirement. It provides a platform to personalize and organize their news feed based on their interest. The main purpose of implementing this system is to increase the accessibility of important notices. It classifies the messages category wise. Latent Dirichlet Allocation (LDA) topic modeling technique is used to achieve the goal of this work. LDA algorithm is “generative probabilistic model” basically works on discrete data. This work is validated using a data set taken from “newsapi.org”.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Blei, D., Ng, A., Jordan, M.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(5), 993–1022 (2003)
Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A.: Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41(6), 391–407 (1990)
Forman, G., Guyon, I., Elisseeff, A.: An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3(7–8), 1289–1305 (2003)
Tong, Z., Zhang, H.: A text mining research based on LDA topic modelling. In: Conference: The Sixth International Conference on Computer Science, Engineering and Information Technology, pp. 201–210 (2016)
Kou, Z.: Stacked graphical learning. Ph.D. thesis, School of Computer Science, Carnegie Mellon University, December 2007
Li, J., Sun, M.: Scalable term selection for text categorization. In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Learning (EMNLP-CoNLL), pp. 774–782 (2007)
Kang, J.H., Lerman, K., Getoor, L.: LA-LDA: a limited attention topic model for social recommendation. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds.) Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013. Lecture Notes in Computer Science, vol. 7812. Springer, Heidelberg (2013)
Porteous, I., Newman, D., Ihler, A., Asuncion, A., Smyth, P., Welling, M.: Fast collapsed Gibbs sampling for latent Dirichlet allocation. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, New York (2008)
Salton, G., Wong, A., Yang, A.C.S.: A vector space model for automatic indexing. Commun. ACM 18, 229–237 (1975)
Teh, Y.W., Jordan, M.I., Beal, M.J., Blei, D.M.: Hierarchical Dirichlet processes. J. Am. Stat. Assoc. 101(476), 1566–1581 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Sarkar, P., Sah, N., Pradhan, A. (2020). INSIDER: An Android Application for Automatic Categorization of News Items by Using LDA. In: Dawn, S., Balas, V., Esposito, A., Gope, S. (eds) Intelligent Techniques and Applications in Science and Technology. ICIMSAT 2019. Learning and Analytics in Intelligent Systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_29
Download citation
DOI: https://doi.org/10.1007/978-3-030-42363-6_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-42362-9
Online ISBN: 978-3-030-42363-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)