Proceedings of the International Conference on Signal, Networks, Computing, and Systems pp 297-301 | Cite as
Live News Streams Extraction for Visualization of Stock Market Trends
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Abstract
The live news data is vital role in the movement of stock prices. The real time unstructured data is generated through electronic and online news sources. Text mining is used for preprocessing of news stories from web sources. The visualization of stock trends can be correlated with actual market prices. The proposed analysis on current news stories helps to predict stock trends. Other techniques like tagging of stock related terms can be added for improvement in results. Stock market trends can be captured with help of this technique.
Keywords
Text mining Stock market News streams Word cloudReferences
- 1.Feldman, R., Sanger J.: The Text Mining Handbook :Advanced Approaches in Analyzing Unstructured Data. Cambridge University Press New York (2007)Google Scholar
- 2.Unstructured Data. Proceedings of the 33rd international conference on Very large data bases (VLDB ’07), Vienna, Austria, pp. 1045–1056, September 23-28, 2007.Google Scholar
- 3.Buneman P., Davidson S., Fernandez M., Suciu D.: Adding structure to unstructured data. Database Theory-ICDT’97, (1997) 336–350Google Scholar
- 4.Anandarajan, M., Anandarajan, A. ed. : e-Research collaboration: Theory, techniques and challenges. Springer Science & Business Media, 2010.Google Scholar
- 5.Schumaker R., Chen H.: Textual analysis of stock market prediction using financial news articles. AMCIS 2006 Proceedings (2006) 185Google Scholar
- 6.Majumder M., Hussian M.A.: Forecasting Of Indian Stock Market Index Using Artificial Neural Network. Information Science (2007) 98–105.Google Scholar
- 7.Vui C. S., Soon G. K., On C. K., Alfred R., Anthony P.: A review of stock market prediction with Artificial neural network (ANN). Control System, Computing and Engineering (ICCSCE), Proceedings -2013 IEEE International Conference (2013) 477 – 482Google Scholar
- 8.Venugopal K. R., Srinivasa K. G., Patnaik L. M. : Fuzzy Based Neuro - Genetic Algorithm for Stock Market Prediction. Soft Computing for Data Mining Applications .Volume 190 of the series Studies in Computational Intelligence. Springer Berlin Heidelberg (2009)139–166Google Scholar
- 9.Annau M.: Short Introduction to tm.plugin.webmining. https://cran.r-project.org/web/packages/tm.plugin.webmining/vignettes/ShortIntro.pdf (Accessed on 15 July, 2015)
- 10.Nagar A., Hahsler M.: Using Text and Data Mining Techniques to extract Stock Market Sentiment from Live News Streams. IACSIT Press, Singapore, Vol. 47 (2012) 91–96Google Scholar
- 11.Weiss S. M., Indurkhya N., Zhang, T., Damerau, F.: Text mining: predictive methods for analyzing unstructured information. Springer Science & Business Media, (2010).Google Scholar
- 12.Chowdhury S. G., Routh S., Chakrabarti S.: News Analytics and Sentiment Analysis to Predict Stock Price Trends. International Journal of Computer Science and Information Technologies, Vol. 5, Issue 3 (2014) 3595–3604.Google Scholar
- 13.Mansuri I. R., Sarawagi S.: Integrating unstructured data into relational databases. Proceedings of the 22nd IEEE International Conference on Data Engineering (ICDE’06), (2006) 29–29Google Scholar
- 14.Rao R.: From unstructured data to actionable intelligence. IT professional. Vol. 5, Issue 6 (2003) 29–35CrossRefGoogle Scholar
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