Abstract
Journal searching for particular context is nowadays a very challenging task because of the large availability of journals and also the finding reputed journals with impact factors also one of the tedious job. Our aim is to reduce the long procedure for journal searching using modern techniques. Applications in machine learning have witnessed a booming interest from last decade. The proposed work uses machine learning algorithm with NoSQL database for keyword-based journal retrieval. The complete work is divided into three subworks: (i) keywords modeling, (ii) journal categorization, and (iii) information retrieval of journal. The journal is categorized based on the keyword. The journal and their keywords are trained using deep neural network. For the given keyword, the similar keywords are extracted. The information retrieval gives the details of the journals for the appropriate keywords. The journal details are maintained in the NoSQL database, and the details are retrieved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tang, B., He, H., Baggenstoss, P.M., Kay, S.: A Bayesian classification approach using class-specific features for text categorization. IEEE Trans. Knowl. Data Eng. 11, 1602—1606 (2016)
Wang, P., Xu, B., Heng, C., Hongwei, F.: Semantic expansion using word embedding clustering and convolution neural network for improving short text classification. Neuro Comput. 74, 806–814 (2016)
Schmidhuber, J.: Deep learning in neural networks: an overview. Neural Netw. 61, 85–117 (2015)
Dasari, D.B., Venu Gopala Rao, K.: Text categorization and machine learning methods: current state of the art. Glob. J. Comput. Sci. Technol. Softw. Data Eng. 1 806–814 (2012)
Zamani, H., Bruce Croft, W.: Relevance-based Word Embedding. arXiv preprint arXiv:1705.03556 (2017)
Sharma, S., Tim, U.S., Gadia, S., Wong, J., Shandilya, R., Peddoju, S.K.: Classification and comparison of NoSQL big data models. Int. J. Big Data Intell. 2(3), 201–221 (2015)
Sharma, S., Shandilya, R., Patnaik, S., Mahapatra, A.: Leading NoSQL models for handling Big Data: a brief review. Int. J. Bus. Inf. Syst. 22(1), 1–25 (2016)
Cerisara, C., Kral, P., Lenc, L.: On the effects of using word2vec representations in neural networks for dialogue act recognition. Comput. Speech Lang. 47, 175–1193 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Revathi, T., Rajalaxmi, T.M. (2019). Keyword-Based Journal Categorization Using Deep Learning. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_56
Download citation
DOI: https://doi.org/10.1007/978-981-13-1592-3_56
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1591-6
Online ISBN: 978-981-13-1592-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)