Discovering the Patterns of Human Interaction in Meetings using Tree Based Mining

Authors(2) :-V. Lakshma Reddy, A. Amruthavalli

Discovering semantic learning is noteworthy for comprehension and translating how individuals collaborate in a meeting exchange. In this paper, we propose a mining technique to remove regular examples of human connection taking into account the caught substance of eye to eye gatherings. Human cooperation’s, for example, proposing a thought, giving remarks, and communicating a positive assessment, demonstrate client aim toward a point or part in a talk. Human cooperation stream in an exchange session is spoken to as a tree. Tree based communication mining calculations are intended to investigate the structures of the trees and to concentrate association stream designs. The trial results demonstrate that we can effectively separate a few fascinating examples that are valuable for the elucidation of human conduct in meeting talks, for example, deciding regular communications, commonplace cooperation streams, and connections between various sorts of collaborations.

Authors and Affiliations

V. Lakshma Reddy
Department of Computer Science and Engineering, PACE Institute of Technology & Sciences, Ongole, Andhra Pradesh, India
A. Amruthavalli
Department of Computer Science and Engineering, PACE Institute of Technology & Sciences, Ongole, Andhra Pradesh, India

Tree Based Mining, Human Collaboration , Framework, Information Mining

  1. W. Geyer, H. Richter, and G.D. Abowd, “Towards a Smarter Meeting Record—Capture and Access of Meetings Revisited,”Multimedia Tools and Applications, vol. 27, no. 3, pp. 393-410, 2005.
  2. S. Junuzovic, R. Hegde, Z. Zhang, P. Chou, Z. Liu, and C. Zhang, “Requirements and Recommendations for an Enhanced Meeting Viewing Experience,” Proc. ACM Int’l Conf. Multimedia, pp. 539- 548, 2008.
  3. K. Otsuka, H. Sawada, and J. Yamato, “Automatic Inference of Cross-Modal Nonverbal Interactions in Multiparty Conversations,” Proc. Int’l Conf. Multimodal Interfaces (ICMI ’07), pp. 255- 262, 2007.
  4. P. Chiu, A. Kapuskar, S. Reitmeier, and L. Wilcox, “Room with a Rear View: Meeting Capture in a Multimedia Conference Room,” IEEE Multimedia, vol. 7, no. 4, pp. 48-54, Oct.-Dec. 2000.
  5. A. Nijholt, R.J. Rienks, J. Zwiers, and D. Reidsma, “Online and Off-Line Visualization of Meeting Information and Meeting Support,” The Visual Computer: Int’l J. Computer Graphics, vol. 22, no. 12, pp. 965-976, 2006.
  6. J.M. DiMicco, K.J. Hollenbach, A. Pandolfo, and W. Bender, “The Impact of Increased Awareness while Face-to-Face,” Human- Computer Interaction, vol. 22, no. 1, pp. 47-96, 2007.
  7. Z. Yu, M. Ozeki, Y. Fujii, and Y. Nakamura, “Towards Smart Meeting: Enabling Technologies and a Real-World Application,” Proc. Int’l Conf. Multimodal Interfaces (ICMI ’07), pp. 86-93, 2007.
  8. S. Junuzovic, R. Hegde, Z. Zhang, P. Chou, Z. Liu, and C. Zhang, “Requirements and Recommendations for an Enhanced Meeting Viewing Experience,” Proc. ACM Int’l Conf. Multimedia, pp. 539-548, 2008.
  9. Z. Yu and Y. Nakamura, “Smart Meeting Systems: A Survey of State-of-the-Art and Open Issues,” ACM Computing Surveys, vol. 42, no. 2, article 8, Feb. 2010.
  10. R. Stiefelhagen, J. Yang, and A. Waibel, “Modeling Focus of Attention for Meeting Indexing Based on Multiple Cues,” IEEE Trans. Neural Networks, vol. 13, no. 4, pp. 928-938, July 2002.
  11. I. Mccowan, D. Gatica-Perez, S. Bengio, G. Lathoud, M. Barnard, and D. Zhang, “Automatic Analysis of Multimodal Group Actions in Meetings,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 305-317, Mar. 2005.
  12. A. Nijholt, R.J. Rienks, J. Zwiers, and D. Reidsma, “Online and Off-Line Visualization of Meeting Information and Meeting Support,” The Visual Computer: Int’l J. Computer Graphics, vol. 22, no. 12, pp. 965-976, 2006.
  13. K. Otsuka, H. Sawada, and J. Yamato, “Automatic Inference of Cross-Modal Nonverbal Interactions in Multiparty Conversations,” Proc. Int’l Conf. Multimodal Interfaces (ICMI ’07), pp. 255- 262, 2007.
  14. J.M. DiMicco, K.J. Hollenbach, A. Pandolfo, and W. Bender, “The Impact of Increased Awareness while Face-to-Face,” Human- Computer Interaction, vol. 22, no. 1, pp. 47-96, 2007.
  15. R. Bakeman and J.M. Gottman, Observing Interaction: An Introduction to Sequential Analysis. Cambridge Univ. Press, 1997.
  16. M.S. Magnusson, “Discovering Hidden Time Patterns in Behavior: T-Patterns and Their Detection,” Behavior Research Methods, Instruments and Computers, vol. 32, no. 1, pp. 93-110, 2000.
  17. L. Anolli, S. Duncan Jr, M.S. Magnusson, and G. Riva, “The Hidden Structure of Interaction: From Neurons to Culture Patterns,” Emerging Communication: Studies in New Technologies and Practices in Communication, IOS Press, Apr. 2005.
  18. K. Gudberg, M. Johnson, T. Anguera, P. Sa´nchez-Algarra, C. Olivera, J. Ssantos, J. Campanico, M. Castan˜ er, C. Torrents, M. Dinu_sova´ , J. Chaverri, O. Camerino, and M.S. Magnusson, “Application of T-Pattern Detection and Analysis in Sport Research,” Open Sports Sciences J., vol. 3, pp. 95-104, 2009.
  19. G. Casas-Garriga, “Discovering Unbounded Episodes in Sequential Data,” Proc. European Conf. Principles and Practice of Knowledge Discovery in Databases (PKDD ’03), pp. 83-94, 2003.
  20. T. Morita, Y. Hirano, Y. Sumi, S. Kajita, and K. Mase, “A Pattern Mining Method for Interpretation of Interaction,” Proc. Int’l Conf. Multimodal Interfaces (ICMI ’05), pp. 267-273, 2005.
  21. Y. Sawamoto, Y. Koyama, Y. Hirano, S. Kajita, K. Mase, K. Katsuyama, K. Yamauchi, “Extraction of Important Interactions in Medical Interviews Using Nonverbal Information,” Proc. Int’l Conf. Multimodal Interfaces (ICMI ’07), pp. 82-85, 2007.
  22. Y. Liu, L. Chen, J. Pei, Q. Chen, and Y. Zhao, “Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays,” Proc. Fifth IEEE Int’l Conf. Pervasive Computing and Comm. (PerCom ’07), pp. 37-46, 2007.
  23. H. Cao, N. Mamoulis, and D.W. Cheung, “Mining Frequent Spatio-Temporal Sequential Patterns,” Proc. Fifth IEEE Int’l Conf. Data Mining (ICDM ’05), pp. 82-89, 2

Publication Details

Published in : Volume 2 | Issue 2 | March-April 2016
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 327-331
Manuscript Number : IJSRSET1622101
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

V. Lakshma Reddy, A. Amruthavalli, " Discovering the Patterns of Human Interaction in Meetings using Tree Based Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.327-331, March-April-2016.
Journal URL : http://ijsrset.com/IJSRSET1622101

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