Enhanced Conference Organization Based On Correlation of Web Information and Ontology Based Expertise Search
From the importance of the conference and its
constructive role in the studies discussion, there must be a strong
organization that allows the exploitation of the discussions in opening
new horizons. The vast amount of information scattered across the
web, make it difficult to find experts, who can play a prominent role
in organizing conferences. In this paper we proposed a new approach
of extracting researchers- information from various Web resources
and correlating them in order to confirm their correctness. As a
validator of this approach, we propose a service that will be useful to
set up a conference. Its main objective is to find appropriate experts,
as well as the social events for a conference. For this application we
us Semantic Web technologies like RDF and ontology to represent
the confirmed information, which are linked to another ontology
(skills ontology) that are used to present and compute the expertise.
[1] H. KAUNTZ and B. SELMAN. Referral web: Combining social
networks and collaborative filtering. Communications of the ACM, 403,
63-65.
[2] J. ZHU and M. EISENSTADT. Buddyfinder-corder: Leveraging social
networks for matchmaking by opportunistic discovery. ISWC2005,
Galway Ireland.
[3] C. Delalonde and E. Soulier. Collaborative Information Retrieval in
R&D distributed teams. 13th International Conference on Concurrent
Engineering, Sophia-Antipolis.
[4] P. Mika. Flink: Semantic Web technology for the extraction and analysis
of social networks. Journal of Web Semantics (2005).
[5] D. Brickley and L. Miller: FOAF Vocabulary Specification. FOAF
Project, http://xmlns.com/foaf/0.1/. (2004).
[6] Remo Lemma. Ebon: Visualizing the DBLP Database (June 17, 2010).
[7] Glaser, H., Millard, I.C.: RKBPlatform: Opening up Services in the Web
of Data. In: International Semantic Web Conference (2009)
[8] J. Tang, J. Zhang, L. Yao, J. Li, L. Zhang, and Z. Su. ArnetMiner:
Extraction and Mining of Academic Social Networks. Proc. of 14th Intl.
Conf. on Knowledge Discovery and Data Mining (SIGKDD 2008).
Henderson, Nevada, 2008, pp.990-998.
[9] Juanzi LI, Jie TANG, Jing ZHANG, Qiong LUO, Yunhao LIU, Mingcai
HONG. Arnetminer: expertise oriented search using social networks.
Frontiers of Computer Science in China, 2008: 94~105.
[10] The VIKEF Consortium, VIKEF Technology Catalogue (January 2007).
[11] C-Y. Lin, N. Cao, S. X. Liu, S. Papadimitriou, J. Sun and X. Yan.
SmallBlue: Social Network Analysis for Expertise Search and Collective
Intelligence. IEEE International Conference on Data Engineering.
[12] A. Kardan, A. Omidvar and F. Farahmandnia. Expert Finding on Social
Network with Link Analysis Approach. 19th Iranian Conference on
Electrical Engineering (ICEE), 2011 Page(s): 1- 5.
[13] J. Tang, J. Zhang, D. Zhang, L. Yao, C. Zhu and J. Li .ArnetMiner: An
Expertise Oriented Search System for Web Community.
[14] J. Zhang, J. Tang, and J. Li. Expert Finding in a Social Network. In:
DASFAA 2007. LNCS, vol. 4443, pp. 1066-1069. Springer, Heidelberg
(2007).
[15] E. Smirnova. A Model for Expert Finding in Social Networks.
Proceeding SIGIR '11 Proceedings of the 34th international ACM SIGIR
conference on Research and development in Information Retrieval Pages
1191-1192 New York, NY, USA ┬®2011. C.
[16] Baldassarre, E. Daga, A. Gangemi, A. Gliozzo, A. Salvati, and Gianluca
Troiani. Semantic Scout: Making Sense of Organizational Knowledge.
EKAW2010.
[17] E. A. Jansen. A Semantic Web based approach to expertise finding at
KPMG.(2010)
[18] C. C. Chou, K. H. Yang, and H. M. Lee. AEFS: Authoritative Expert
Finding System Based on a Language Model and Social Network
Analysis.(2007)
[19] K. H. Yang, C. Y. Chen, H. M. Lee, and J.M. Ho. EFS: Expert Finding
System based on Wikipedia Link Pattern Analysis. 2008 IEEE
International Conference on Systems, Man and Cybernetics (SMC
2008).
[20] R. Punnarut and G. Sriharee. A Researcher Expertise Search System
using Ontology-Based Data Mining. Seventh Asia-Pacific Conference
on Conceptual Modelling (APCCM 2010), Brisbane, Australia, January
2010.
[1] H. KAUNTZ and B. SELMAN. Referral web: Combining social
networks and collaborative filtering. Communications of the ACM, 403,
63-65.
[2] J. ZHU and M. EISENSTADT. Buddyfinder-corder: Leveraging social
networks for matchmaking by opportunistic discovery. ISWC2005,
Galway Ireland.
[3] C. Delalonde and E. Soulier. Collaborative Information Retrieval in
R&D distributed teams. 13th International Conference on Concurrent
Engineering, Sophia-Antipolis.
[4] P. Mika. Flink: Semantic Web technology for the extraction and analysis
of social networks. Journal of Web Semantics (2005).
[5] D. Brickley and L. Miller: FOAF Vocabulary Specification. FOAF
Project, http://xmlns.com/foaf/0.1/. (2004).
[6] Remo Lemma. Ebon: Visualizing the DBLP Database (June 17, 2010).
[7] Glaser, H., Millard, I.C.: RKBPlatform: Opening up Services in the Web
of Data. In: International Semantic Web Conference (2009)
[8] J. Tang, J. Zhang, L. Yao, J. Li, L. Zhang, and Z. Su. ArnetMiner:
Extraction and Mining of Academic Social Networks. Proc. of 14th Intl.
Conf. on Knowledge Discovery and Data Mining (SIGKDD 2008).
Henderson, Nevada, 2008, pp.990-998.
[9] Juanzi LI, Jie TANG, Jing ZHANG, Qiong LUO, Yunhao LIU, Mingcai
HONG. Arnetminer: expertise oriented search using social networks.
Frontiers of Computer Science in China, 2008: 94~105.
[10] The VIKEF Consortium, VIKEF Technology Catalogue (January 2007).
[11] C-Y. Lin, N. Cao, S. X. Liu, S. Papadimitriou, J. Sun and X. Yan.
SmallBlue: Social Network Analysis for Expertise Search and Collective
Intelligence. IEEE International Conference on Data Engineering.
[12] A. Kardan, A. Omidvar and F. Farahmandnia. Expert Finding on Social
Network with Link Analysis Approach. 19th Iranian Conference on
Electrical Engineering (ICEE), 2011 Page(s): 1- 5.
[13] J. Tang, J. Zhang, D. Zhang, L. Yao, C. Zhu and J. Li .ArnetMiner: An
Expertise Oriented Search System for Web Community.
[14] J. Zhang, J. Tang, and J. Li. Expert Finding in a Social Network. In:
DASFAA 2007. LNCS, vol. 4443, pp. 1066-1069. Springer, Heidelberg
(2007).
[15] E. Smirnova. A Model for Expert Finding in Social Networks.
Proceeding SIGIR '11 Proceedings of the 34th international ACM SIGIR
conference on Research and development in Information Retrieval Pages
1191-1192 New York, NY, USA ┬®2011. C.
[16] Baldassarre, E. Daga, A. Gangemi, A. Gliozzo, A. Salvati, and Gianluca
Troiani. Semantic Scout: Making Sense of Organizational Knowledge.
EKAW2010.
[17] E. A. Jansen. A Semantic Web based approach to expertise finding at
KPMG.(2010)
[18] C. C. Chou, K. H. Yang, and H. M. Lee. AEFS: Authoritative Expert
Finding System Based on a Language Model and Social Network
Analysis.(2007)
[19] K. H. Yang, C. Y. Chen, H. M. Lee, and J.M. Ho. EFS: Expert Finding
System based on Wikipedia Link Pattern Analysis. 2008 IEEE
International Conference on Systems, Man and Cybernetics (SMC
2008).
[20] R. Punnarut and G. Sriharee. A Researcher Expertise Search System
using Ontology-Based Data Mining. Seventh Asia-Pacific Conference
on Conceptual Modelling (APCCM 2010), Brisbane, Australia, January
2010.
@article{"International Journal of Information, Control and Computer Sciences:61638", author = "Hassan Noureddine and Maria Sokhn and Iman Jarkass and Elena Mugellini and Omar Abou Khaled", title = "Enhanced Conference Organization Based On Correlation of Web Information and Ontology Based Expertise Search", abstract = "From the importance of the conference and its
constructive role in the studies discussion, there must be a strong
organization that allows the exploitation of the discussions in opening
new horizons. The vast amount of information scattered across the
web, make it difficult to find experts, who can play a prominent role
in organizing conferences. In this paper we proposed a new approach
of extracting researchers- information from various Web resources
and correlating them in order to confirm their correctness. As a
validator of this approach, we propose a service that will be useful to
set up a conference. Its main objective is to find appropriate experts,
as well as the social events for a conference. For this application we
us Semantic Web technologies like RDF and ontology to represent
the confirmed information, which are linked to another ontology
(skills ontology) that are used to present and compute the expertise.", keywords = "Expert finding, Information extraction, Ontologies, Semantic web, Social events.", volume = "7", number = "4", pages = "500-5", }
