Volume 52 | Number 2 | Year 2017 | Article Id. IJMTT-V52P514 | DOI : https://doi.org/10.14445/22315373/IJMTT-V52P514
K Sivaramakrishna, K.Srinivasarao, BV Satish, "Deep Analysis of Textual Data in Multiple formats using Hadoop Techniques," International Journal of Mathematics Trends and Technology (IJMTT), vol. 52, no. 2, pp. 103-113, 2017. Crossref, https://doi.org/10.14445/22315373/IJMTT-V52P514
[1] Xerox Corporation (2015): http://www.xrce.xerox.com/Research-Development/Industry-Expertise/Finance (accessed 26 December 2015).
[2] Apache Opennlp (2015): http://opennlp.apache.org/ (accessed 19 December 2015).
[3] Doug cutting, Marco nicosia, ―About Hadoop http://lucene.apache.org/Hadoop/about.html.
[4] J. R. Finkel, T. Grenager, and C. Manning (2005). ―Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. Proceedings of the 43nd Annual Meeting of the Association for Computational Linguistics (ACL 2005). (online reading: http://nlp. stanford.edu/~manning/papers/gibbscrf3.pdf).
[5] Chakraborty, G., Pagolu, M. & Garla, S (2013). Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. SAS Publishing.
[6] S. Lee and H. Kim (2008). ―News Keyword Extraction for Topic Tracking. Fourth International Conference on Networked Computing and Advanced Information Management, IEEE.
[7] Google Alerts (2016): http://www.google.com/alerts (accessed 10 January 2016).
[8] Seung Jin sul, AndreyTovchigrechko, ―Parallelizing BLAST and SOM algorithms with Mapreduce-MPI library 25th IEEE International Symposium on Parallel and Distributed Processing, IPDPS, 2011.
[9] ATLAS Project (2013): http://www.atlasproject.eu/atlas/project/task/5.1 (accessed 10 January 2016).
[10] G. Wen, G. Chen, and L. Jiang (2006). ―Performing Text Categorization on Manifold. 2006 IEEE International Conference on Systems, Man, and Cybernetics, Taipei, Taiwan, IEEE.
[11] H. Cordobés, A. Fernández Anta, L.F. Chiroque, F. Pérez García, T. Redondo, A. Santos (2014). ―Graph-based Techniques for Topic Classification of Tweets in Spanish―. International Journal of Interactive Multimedia an Artificial Intelligence.
[12] T. Theodosiou, N. Darzentas, L. Angelis, C.A. Ouzonis (2008). ―PuReD- MCL: a graph-based PubMed document clustering methodology. Bioinformatics 24.
[13] Q. Lu, J. G. Conrad, K. Al-Kofahi, W. Keenan (2011). ―Legal document clustering with built-in topic segmentation, Proceedings of the 20th ACM international conference on Information and knowledge management.
[14] P. Cowling, S. Remde, P. Hartley, W. Stewart, J. Stock-Brooks, T. Woolley (2010), ―C-Link Concept Linkage in Knowledge Repositories. AAAI Spring Symposium Series.
[15] C-Link (2015): http://www.conceptlinkage.org/ (accessed 10 December 2015).
[16] Y. Hassan-Montero, and V Herrero-Solana (2006). ―Improving Tag-Clouds as Visual Information Retrieval Interfaces, I International Conference on Multidisciplinary Information Sciences and Technologies, InSciT2006.
[17] Wordle (2014): http://www.wordle.net/ (accessed 20 December 2015).
[18] M. A. Hearst (2009) ―Information Visualization for Text Analysis, in Search User Interfaces. Cambridge University Press (online reading: http://searchuserinterfaces.com/book/).
[19] D3.js (2016): http://d3js.org/ (accessed 20 January 2016).
[20] Gephi (2016) https://gephi.org/ (accessed 20 January 2016).
[21] L. Hirschman, R. Gaizauskas (2001), ―Natural language question answering: the view from here‖, Natural Language Engineering 7. Cambridge University Press [22] OpenEphyra.
[23] N. Schlaefer, P. Gieselmann, and G. Sautter (2006). ―The Ephyra QA system. 2006 Text Retrieval Conference (TREC).
[24] YodaQA (2015): http://ailao.eu/yodaqa/ (accessed 5 January 2016).
[25] P. Baudis (2015) ―YodaQA: A Modular Question Answering System Pipeline. POSTER 2015 — 19th International Student Conference on Electrical Engineering. (online reading: http://ailao.eu/yodaqa/yodaqa- poster2015.pdf).
[26]DL4J (2015): http://deeplearning4j.org/textanalysis.html (accessed 16 December 2015).
[27]Google–Word2vec(2013): http://arxiv.org/pdf/1301.3781.pdf (accessed 20 December 2015).
[28] D. Lazer, R. Kennedy, G. King, and A. Vespignani (2014). ―Big data. The parable of Google Flu: traps in big data analysis. Science, 343(6176).
[29] D. Boyd, and K. Crawford (2011). ―Six Provocations for Big Data. A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. (Available at SSRN: http://ssrn.com/abstract=1926431 or http:// dx.doi.org/10.2139/ssrn.1926431).