Expertise Search in Unstructured Data in ECM using S-BPM Approach

Alexander Gromoff, Julia Stavenko, Kristina Evina, Nikolay Kazantsev

Abstract

This article describes the application of currently most promising methods of graph theory, content analysis and (3) subject-oriented approach to business process modelling for creating and automation of innovative process and therefore for maximization of ROI (return on investments) in intellectual and social capital of enterprises. In a course of development, instant full-text indexation takes place and taxonomic picture of different branches for such community is formed. In due course system gathers the statistics and builds-up maps of intercommunication with priority allocation of most discussed topics. A group of predetermined experts begins discussion on development prospects of this or that subject afterwards. The strategic map of investments into innovative development that can be offered to group of investors for competitive investments eventually turns out. In this process all steps except final (gathering of experts) are human non-dependant, what increase efficiency of the process in general.

References

  1. Noah E., Friedkin & Eugene C. Johnsen: Social Influence Network Theory: A Sociological Examination of Small Group Dynamics (Structural Analysis in the Social Sciences), Cambridge University Press; 1 edition edition (2011)
  2. Burt R., 2001. The Social Capital of structural holes // Guillen M.F., Collins R., England P., Meyer M. (eds.). New Directions in Economic Sociology. N.Y.: Russel Sage Foundation: 201-246.
  3. Fernandez, R. M., Castilla, E. J., & Moore, P. 2000. Social capital at work: Networks and employment at a phone center. American Journal of Sociology, 105: 1288-1356.
  4. Granovetter, M. [1974] 1995. Getting a Job: A Study of Contacts and Careers. Chicago, IL: The University of Chicago Press.
  5. Seidel, M. D. L., Polzer, J. T. & Stewart, K. J., 2000. Friends in high places: The effects of social networks on discrimination in salary negotiations. Administrative Science Quarterly, 45:1-24.
  6. Adler, P. S. & Kwon, S. W., 2002. Social capital: Prospects for a new concept. Academy of Management Review, 27: 17-40.
  7. Xiaodan Song, Belle L. Tseng, Ching-Yung Lin and Ming-Ting Sun, "ExpertiseNet: Relational and Evolutionary Expert Modeling", Intl. Conf. on User Modeling, Edinburgh, UK, July 2005.
  8. Jing Zhang, Jie Tang, Juan-Zi Li: Expert Finding in a Social Network. In Proceedings of DASFAA'2007. pp.10661069.
  9. Yupeng Fu, Rongjing Xiang, Yiqun Liu, Min Zhang, Shaoping Ma: Finding Experts Using Social Network Analysis 2007 IEEE/WIC/ACM International Conference on Web Intelligence.
  10. Borgatti, S. P. & Everett, M. G., (2006). A Graph-Theoretic Perspective on Centrality. Social Networks, 28(4), 466-484.
  11. Wang, J., & Chen, C., (2004). An Automated Tool for Managing Interactions in Virtual Communities - Using Social Netwrok Analysis Approach. Journal of Organizational Computing and Electronic Commerce, 14(1), 1-26.
  12. Wasserman, S. & Faust, K., (1994). Social Network Analysis: Method and Applications.Cambridge, UK: Cambridge University Press.
  13. Ahuja, M., Galletta, D. & Carley, K., (2003). Individual Centrality and Performance in Virtual R&D Groups: An Empirical Examination. Management Science, 49(1).
  14. P. Bonacich, Factoring and weighting approaches to status scores and clique identification, Journal of Mathematical Sociology, 2 (1972).
  15. Watts, D. J.: Collective Dynamics of «Small-world» Networks // Nature / Ed. by S.H.Strogatz. 1998. Vol. 393.
  16. Maron, M. E., Curry, S., Thompson, P.: An Inductive Search System: Theory, Design and Implementation. IEEE Transaction on Systems, Man and Cybernetics, 16(1) (1986), 21-28.
  17. Steeter, L. A., Lochbaum, K. E.: An Expert/Expert Locating System based on Automatic Representation of Semantic Structure. In Proc. of the Fourth IEEE Conference on Artificial Intelligence Applications: San Diego, CA, (1988), 345-349.
  18. Staab, S.: Human language technologies for knowledge management. Intelligent Systems, 16(6): (2001), 84-94.
  19. Bull, S., Greer, J., McCalla, G., Kettel, L., Bowes, J.: User Modelling in I-Help: What, Why, When and How. In Proc. of the 8th International Conference on User Modeling, Sonthofen, Germany, July, (2001), 117-126.
  20. Alexander Gromoff, Valery Chebotarev, Kristin Evina and Yulia Stavenko: An Approach to Agility in Enterprise Innovation S-BPM One Learning by Doing - Doing by Learning Third International Conference, S-BPM One 2011: Springer, 2011.
Download


Paper Citation


in Harvard Style

Gromoff A., Stavenko J., Evina K. and Kazantsev N. (2012). Expertise Search in Unstructured Data in ECM using S-BPM Approach . In Proceedings of the 10th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems and 1st International Workshop on Web Intelligence - Volume 1: WEBI, (ICEIS 2012) ISBN 978-989-8565-14-3, pages 94-105. DOI: 10.5220/0004104800940105


in Bibtex Style

@conference{webi12,
author={Alexander Gromoff and Julia Stavenko and Kristina Evina and Nikolay Kazantsev},
title={Expertise Search in Unstructured Data in ECM using S-BPM Approach},
booktitle={Proceedings of the 10th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems and 1st International Workshop on Web Intelligence - Volume 1: WEBI, (ICEIS 2012)},
year={2012},
pages={94-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004104800940105},
isbn={978-989-8565-14-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems and 1st International Workshop on Web Intelligence - Volume 1: WEBI, (ICEIS 2012)
TI - Expertise Search in Unstructured Data in ECM using S-BPM Approach
SN - 978-989-8565-14-3
AU - Gromoff A.
AU - Stavenko J.
AU - Evina K.
AU - Kazantsev N.
PY - 2012
SP - 94
EP - 105
DO - 10.5220/0004104800940105