International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Emerging Event Based Tweet Structuring Using Multilevel Inverted List

Author : M.Vinoth ¹ C.Kotteeswaran ²

Date of Publication :7th June 2016

Abstract: Tweet stream are a group of small piece of text which usually represented by the vector space model that constructed on real-life and real-time information. Social network information sharing place the vital role in representing importance of the social network that may dynamically change over time. However to detect and monitor the emerging events from the continuous tweet streams remains a critical factor. Here, I wish to propose a novel indexing scheme called multi-layer inverted list to propagated the emerging events on the social networks (eg: Twitter).Thus, I am in search of facilitated methods to replace the exist in searching mechanism , Cosine similarity method, MIL which combination could give better actuality on detecting and monitoring the emerging events. Extensive experiments have been conducted on a large-scale real-life tweet dataset. The results demonstrate the promising performance of our event indexing and watching ways on each potency and effectiveness.

Reference :

1. Takeshi Sakaki and Makoto Okazaki, "Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, PP. 4, April - 2013.
2. Marco Vanetti, Elisabetta Binaghi and Elena Ferrari,"A System to Filter Unwanted Messages from OSN User Walls", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, PP. 2, February -2013.
3. Hongyun Cai, Zi Huang and Divesh Srivastava,"Indexing Evolving Events from Tweet Streams", IEEE Transactions On Knowledge And Data Engineering, Vol. , PP. 4, April -2015.
4. Y. Jie, L. Andrew, C. Mark, R. Bella, and P. Robert, “Using social media to enhance emergency situation awareness,” IEEE Intelligent Systems, vol. 27, no. 6, pp. 52–59, 2012.
5. S. Unankard, X. Li, and M. Sharaf, “Emerging event detection in social networks with location sensitivity,” World Wide Web, pp. 1–25, 2014.
6. A. C. Awekar and N. F. Samatova, “Fast matching for all pairs similarity search.” in Web Intelligence, pp. 295– 300,2009.
7. A. Uszok, J.M. Bradshaw, M. Johnson, R. Jeffers, A. Tate, J. Dalton,and S. Aitken, “Kaos Policy Management for Semantic Web Services,” IEEE Intelligent Systems, vol. 19, no. 4, pp. 32-41, July/Aug. 2004.
8. M. Sarah, C. Abdur, H. Gregor, L. Ben, and M. Roger, “Twitter and the Micro-Messaging Revolution,” technical report, O’Reilly Radar, 2008
9. K. Borau, C. Ullrich, J. Feng, and R. Shen, “Microblogging for Language Learning: Using Twitter to Train Communicative and Cultural Competence,”Proc. Eighth Int’l Conf. Advances in Web Based Learning (ICWL ’09),pp. 78-87, 2009.
1. Takeshi Sakaki and Makoto Okazaki, "Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, PP. 4, April - 2013.
2. Marco Vanetti, Elisabetta Binaghi and Elena Ferrari,"A System to Filter Unwanted Messages from OSN User Walls", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, PP. 2, February -2013.
3. Hongyun Cai, Zi Huang and Divesh Srivastava,"Indexing Evolving Events from Tweet Streams", IEEE Transactions On Knowledge And Data Engineering, Vol. , PP. 4, April -2015
4. Y. Jie, L. Andrew, C. Mark, R. Bella, and P. Robert, “Using social media to enhance emergency situation awareness,” IEEE Intelligent Systems, vol. 27, no. 6, pp. 52–59, 2012.
5. S. Unankard, X. Li, and M. Sharaf, “Emerging event detection in social networks with location sensitivity,” World Wide Web, pp. 1–25, 2014
6. A. C. Awekar and N. F. Samatova, “Fast matching for all pairs similarity search.” in Web Intelligence, pp. 295– 300,2009.
7. A. Uszok, J.M. Bradshaw, M. Johnson, R. Jeffers, A. Tate, J. Dalton,and S. Aitken, “Kaos Policy Management for Semantic Web Services,” IEEE Intelligent Systems, vol. 19, no. 4, pp. 32-41, July/Aug. 2004.
8. M. Sarah, C. Abdur, H. Gregor, L. Ben, and M. Roger, “Twitter and the Micro-Messaging Revolution,” technical report, O’Reilly Radar, 2008
9. K. Borau, C. Ullrich, J. Feng, and R. Shen, “Microblogging for Language Learning: Using Twitter to Train Communicative and Cultural Competence,”Proc. Eighth Int’l Conf. Advances in Web Based Learning (ICWL ’09),pp. 78-87, 2009.