Identifying Trends in Data Science Articles using Text Mining

The research conducted in this paper presents a detailed analysis of the latest research publications related to Data Science using information retrieval and text mining approach. The database used in this study was created by collecting the latest research papers from well-reputed Journals and Conference proceedings published by IEEE and Springer. This comprehensive study shows the significance of information retrieval and text mining in the identification of key insight from textual documents.

[1]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[2]  Johannes K. Chiang,et al.  Machine Learning Trend Anticipation by Text Mining Methodology Based on SSCI Database , 2009, 2009 Fifth International Joint Conference on INC, IMS and IDC.

[3]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[4]  Shusaku Tsumoto,et al.  Trend detection from large text data , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[5]  Sumit Kumar Banshal,et al.  Identifying themes and trends in CS research output from India , 2015, 2015 International Conference on Cognitive Computing and Information Processing(CCIP).

[6]  Shao-Yu Wang,et al.  Examining the Trend of Taiwan Primary and High School Scientific Exhibition by Using Text Mining Technique , 2017, 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI).

[7]  Cole Nussbaumer Knaflic,et al.  Storytelling with Data: A Data Visualization Guide for Business Professionals , 2015 .

[8]  Carlos J. Costa,et al.  Research trends in CISTI's unveiled through text mining , 2017, 2017 12th Iberian Conference on Information Systems and Technologies (CISTI).

[9]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .

[10]  Tao Luo,et al.  Research on topics trends based on weighted K-means , 2017, 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC).

[11]  Yuntai Kim.  Study on Science and Technology Policy trend using text network analysis in Korea , 2016, 2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA).

[12]  Hongqi Han,et al.  Revealing Research Themes and their Evolutionary Trends Using Bibliometric Data Based on Strategic Diagrams , 2013, 2013 International Conference on Information Science and Cloud Computing Companion.

[13]  Colin Fay,et al.  Text Mining with R: A Tidy Approach , 2018 .