The week's pick
Random Articles
Reseach Article
A Real Time Stream Data Processing and Analysis Model and Catchments over Twitter Stream Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 1 |
| Year of Publication: 2017 |
| Authors: Ankit Sarawagi, Rajeev Pandey, Raju Barskar, S. P. Pandey |
10.5120/ijca2017915663
|
Ankit Sarawagi, Rajeev Pandey, Raju Barskar, S. P. Pandey . A Real Time Stream Data Processing and Analysis Model and Catchments over Twitter Stream Data. International Journal of Computer Applications. 179, 1 ( Dec 2017), 22-33. DOI=10.5120/ijca2017915663
Abstract
Big data processing is an important aspect in todays world. Twitter produce a large number of tweets and different segment of data according user usage and post. Understanding the proper sentiments, extracting the proper meaning from it is an objective task which is required different processing tools and methodology. Real time data gathering, storing them and analyzing efficiently to produce effective and fast accessible result approach is always a required work today. For this purpose in this research work a technique PSWNSWAP is proposed, which use Twitter stream data gathering in real time as well as Fast indexing, processing and performed sentiment analysis of gathered data. Distance computation, finding the right place to perform some operation is the tedious task for business operation or any brand to get established in new areas. Here’s an algorithm which is St-QAP algorithm, is investigated and processed with the Apache Storm tool and NLP library. The Objective is to produce an efficient path mapping and catchments for new brands to establish in a new area and solving investigation behind it. Our proposed algorithm computed efficient result, while comparing with existing traditional solution with it.
References
- Saeed Shahrivari, “Beyond Batch Processing: Towards Real-Time and Streaming Big Data”, Computers, Vol. 3, pp. 117.129, 2014.
- Intel IT center. Big Data in the Cloud: Converging Technologies [online]. Available: http://www.intel.com/content/www/us/en/big-data/big-data-cloud-technologies-brief.html. Date accessed: (April 2015).
- Jos´e Antonio Iglesias, Aaron Garc´ıa-Cuerva, Agapito Ledezma and Araceli Sanchis, "Social Network Analysis: Evolving Twitter Mining", 2016 IEEE International Conference on Systems, Man, and Cybernetics • SMC 2016 |October 9-12, 2016 • Budapest, Hungary
- Susan Gunelius, The Data Explosion in 2014 [Online]. Available: http://aci.info/2014/07/12/the-data-explosion-in-2014-minute-by-minute-infographic/ Date accessed: July 12, 2014.
- Xabier Artola, Zuhaitz Beloki, German Rigau, Aitorsoroa “Big data for natural language processing: A Streaming Approach“ in knowledge-based systems volume 79, May 2015, pages 36–42.
- Bharati Punjabi, Sonal Honale, "A Research on Big Data Analysis & Processing With Data Mining Techniques", International Journal of Scientific Engineering and Applied Science (IJSEAS) - Volume-1, Issue-9, December 2015.
- Walaa Medhat, Ahmed Hassan, Hoda Korashy,"Sentiment analysis algorithms and applications:A survey"Production and hosting by Elsevier B.V. on behalf of Ain Shams University.accepted 19 April 2014Available online 27 May 2014.
- "Big Data Analytics: managing business data costs and data quality in the capital markets, available online-https://www.emc.com/collateral/software/white-papers/h10834-business-data-cost-optimization-wp.pdf.
- L.Jaba Sheela, "A Review of Sentiment Analysis in Twitter Data Using Hadoop", International Journal of Database Theory and Application, Vol.9, No.1(2016), pp.77-86, http://dx.doi.org/10.14257/ijdta.2016.9.1.07.
- S.K. Bharti n, B.Vachha, R.K.Pradhan, K.S.Babu, S.K.Jena, “Sarcastic sentiment detection in tweets streamed in real time: a big data approach” Contents lists available at Science Direct Digital Communications and Networks, Accepted 15 June 2016 , Available online 12 July 2016
- M. R. Evans, D. Oliver, K. Yang, X. Zhou, S. Shekhar, “Enabling Spatial Big Data via CyberGIS: Opportunities and Challenges,” M. F. Goodchild, Ed. S. Wang, CyberGIS: Fostering a New Wave of Geospatial Innovation and Discovery. Springer, 2014.
- Alyson Lloyd, James Cheshire, “Deriving retail centre locations and catchments from geo-tagged Twitter data” , Contents lists available at Science Direct Computers, Environment and Urban Systems, Article Accepted 28 September 2016 , Available online 20 October 2016.
- J.P. Nivash, Ebin Deni Raj , L.D. Dhinesh Babu, M. Nirmala, V. Manoj Kumar, "Analysis on enhancing storm to efficiently process big data in real time', Published in: Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference, Date of Conference: 11-13 July 2014.Publisher: IEEE, Date Added to IEEE Xplore: 23 April 2015.
- Thanh Trung Nguyen,Tin Khac Vu, Minh Hieu Nguyen,"BFC: High-Performance Distributed Big-File CloudStorage Based On Key-Value Store",978-1-4799-8676-7/15copyright 2015 IEEE,SNPD 2015, June 1-3 2015, Takamatsu, Japan.
Index Terms
Keywords