Abstract
We have applied social network analysis (SNA) approach for our current researches that relate to recommender systems in the field of scientific research. One of the challenges for SNA based methods is how to identify and quantify relationships of actors in a specified social community. In this context, how we can extract and organize a social structure from a collection of scientific articles. In order to do so, we proposed and developed a collaborative knowledge model of researchers from their publishing activities. The collaborative knowledge model (CKM) forms a collaborative network that is used to represent, qualify collaborative relationships. The proposed model is based on the combination of graph theory and probability theory. The model consists of three key components such as CoNet (a scientific collaborative network), M (measures) and R (rules). The model aims to support recommendations for researchers such as research paper recommendation, collaboration recommendation, expert recommendation, and publication venue recommendation that we have been working on.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abbasi, A., Altmann, J.: A social network system for analyzing publication activities of researchers. TEMEP Discussion Papers 201058, Seoul National University, Technology Management, Economics, and Policy Program, TEMEP (2010)
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. on Knowl. and Data Eng. 17, 734–749 (2005)
Chen, H.H., Gou, L., Zhang, X., Giles, C.L.: Collabseer: a search engine for collaboration discovery. In: Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries, JCDL 2011, pp. 231–240. ACM, New York (2011)
Ekstrand, M.D., Kannan, P., Stemper, J.A., Butler, J.T., Konstan, J.A., Riedl, J.T.: Automatically building research reading lists. In: Proceedings of the Fourth ACM Conference on Recommender Systems, RecSys 2010, pp. 159–166. ACM, New York (2010)
Giles, C.L., Bollacker, K.D., Lawrence, S.: Citeseer: an automatic citation indexing system. In: Proceedings of the Third ACM Conference on Digital Libraries, DL 1998, ACM, New York (1998)
Huynh, T., Luong, H., Hoang, K., Gauch, S., Do, L., Tran, H.: Scientific publication recommendations based on collaborative citation networks. In: Proceedings of the 3rd International Workshop on Adaptive Collaboration (AC 2012) as part of The 2012 International Conference on Collaboration Technologies and Systems (CTS 2012), Denver, Colorado, USA, pp. 316–321 (2012)
Jones, P.M.: Collaborative knowledge management, social networks, and organizational learning. In: Proceedings of the Ninth International Conference on Human-Computer Interaction, pp. 310–314. Lawrence Erlbaum Associates (2001)
Kirchhoff, L.: Applying Social Network Analysis to Information Retrieval on the World Wide Web. Ph.D. thesis, the University of St. Gallen, Graduate School of Business Administration, Economics, Law and Social Sciences (HSG) (2010)
Kirchhoff, L., Stanoevska-Slabeva, K., Nicolai, T., Fleck, M., Stanoevska, K.: Using social network analysis to enhance information retrieval systems. In: Applications of Social Network Analysis (ASNA), Zurich, vol. 7, pp. 1–21 (2008)
Lawrence, S., Giles, C.L., Bollacker, K.: Digital libraries and autonomous citation indexing. Computer 32, 67–71 (1999)
Leicht, E.A., Holme, P., Newman, M.E.J.: Vertex similarity in networks. Phys. Rev. EÂ 73, 026120 (2006), http://link.aps.org/doi/10.1103/PhysRevE.73.026120
Li, C.P.W.: Research paper recommendation with topic analysis. In: 2010 International Conference on Computer Design and Applications (ICCDA), pp. 264–268. IEEE (2010)
Liu, Q., Tang, C., Qiao, S., Liu, Q., Wen, F.: Mining the Core Member of Terrorist Crime Group Based on Social Network Analysis. In: Yang, C.C., Zeng, D., Chau, M., Chang, K., Yang, Q., Cheng, X., Wang, J., Wang, F.-Y., Chen, H. (eds.) PAISI 2007. LNCS, vol. 4430, pp. 311–313. Springer, Heidelberg (2007)
Lopes, G.R., Moro, M.M., Wives, L.K., De Oliveira, J.P.M.: Collaboration recommendation on academic social networks. In: Proceedings of the 2010 International Conference on Advances in Conceptual Modeling: Applications and Challenges. ER 2010, pp. 190–199. Springer, Heidelberg (2010)
Luong, H., Huynh, T., Gauch, S., Do, L., Hoang, K.: Publication Venue Recommendation Using Author Network’s Publication History. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ACIIDS 2012, Part III. LNCS, vol. 7198, pp. 426–435. Springer, Heidelberg (2012)
Müller-Prothmann, T.: Social network analysis: A practical method to improve knowledge sharing. In: Hands-On Knowledge Co-Creation and Sharing, pp. 219–233 (2007)
Ohta, M., Hachiki, T.T.A.: Related paper recommendation to support online-browsing of research papers. In: 2011 Fourth International Conference on Applications of Digital Information and Web Technologies (ICADIWT), pp. 130–136 (2011)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web (1998)
Xu, J.J., Chen, H.: Crimenet explorer: a framework for criminal network knowledge discovery. ACM Trans. Inf. Syst. 23(2), 201–226 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huynh, T., Hoang, K. (2012). Modeling Collaborative Knowledge of Publishing Activities for Research Recommendation. In: Nguyen, NT., Hoang, K., JÈ©drzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34630-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-34630-9_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34629-3
Online ISBN: 978-3-642-34630-9
eBook Packages: Computer ScienceComputer Science (R0)