Knowledge Discovery From Expert Profile Processing - The Expert Finding Solutions For Pet Domain
Minakshi Gujral, Satish Chandra
Keywords : Expert finding systems; Knowledge discovery; Recommendation systems; Information Systems; Expert locating systems; Pet recommendation systems; Pet Finding systems; Vet locating systems; Vet Finding Systems.
ABSTRACT: The Expert Finding Systems are gaining focus in Universities, HR, Medical and Project Management systems. These systems are way ahead of recommendation systems, which are an extensive class of Web applications that involve predicting user responses to options. Expert Finding Systems look beyond the best-fit expert to solve the end user’s problems. These problems can be a query regarding some item, solution, service or trouble shooting some case scenario. This area of research encompasses Artificial Intelligence, Web application engineering and also Software Engineering used to validate the simulated responses of this system. This paper talks about an expert finding system in pet domain. The expertise in Pet Domain can be in form of Doctor, trainer, breeder, groomer or Dog Shelter organizations. The real challenges are to recognize the problem scenario, understand the user, data and the environment, taking care of feasibility and then giving the novice user, the best fit solution for his pet. The goal is requirement analysis for best fit search foraying in array of choices of this ever changing E-world and Recommendation architecture which provides contemporary problems in every search engine and recommendation system’s research. This paper addresses all this and assists the user to find their requirements easily and undermine the information overloading as well as over specialization problems along with other recommendation issues.
 J.S. Bridle, “Probabilistic Interpretation of Feedforward Classifi-cation Network Outputs, with Relationships to Statistical Pattern Recognition,” Neurocomputing—Algorithms, Architectures and Applications, F. Fogelman-Soulie and J. Herault, eds., NATO ASI Series F68, Berlin: Springer-Verlag, pp. 227-236, 1989. (Book style with paper title and editor)
 David W. McDonald and Mark S. Ackerman : Just Talk to Me: A Field Study of Expertise Location, Proceedings of the 1998 ACM CSCW.
 Adriana Vivacqua and Henry Lieberman : Agents to Assist in Finding Help, Media Laboratory, MIT, Cambridge.
 M. Naeem, M. Bilal Khan, M. Tanvir Afzal: Expert discovery: A web mining approach, JAIDM , 19 February 2013.
 [Maryam Karimzadehgan, Ryen W. White, and Matthew Rich-ardson : Enhancing Expert Finding Using Organizational Hierar-chies, Microsoft Research, One Microsoft Way, Redmond (plz see if this one isin proper format).
 Mark T. Maybury : Expert Finding Systems, MTR 06B000040, MITRE TECHNICAL REPORT, September 2006.
 Dawit YIMAM-SEID, Alfred KOBSA : Expert Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach, Journal of Organizational Computing and Electronic Commerce 13(1), 2003, 1-24.
 Fawaz Alarfaj, Udo Kruschwitz, David Hunter and Chris Fox: Finding the Right Supervisor: Expert-Finding in a University Domain, Proceedings of the NAACL HLT 2012 Student Research Workshop, pages 1–6.
 Gujral, M. and Asawa, K., Recommendation Systems – The Knowledge Engineering analysis for the best fit decisions ,Second International Conference on Advances in Computer Engineering – ACE 2011, Trivandrum, Kerala, INDIA. Page No 204-207.
 Minakshi Gujral, Dr Satish Chandra, "Beyond Recommenders and Expert Finders, processing the Expert Knowledge,IJCSI In-ternational Journal of Computer Science Issues, Vol 11, Issue 1, No 2,January 2014, Page No 151 -158.
 [Minakshi Gujral, Dr Satish Chandra, "Beyond One shot rec-ommendations: The seamless interplay of environmental para-meters and Quality of recommendations for the best fit list, ACSIJ International Journal of Advances in Computer Science, Vol, 03, Issue 1, No. 07, January 2014, Page No 57 – 66.
 Gujral, M. and Chandra, Satish., “Knowledge Synthesis of rec-ommendation systems-Finding expert recommendations for cuisines,” unpublished.
 Mowbray, B. Challenges in Locating Experts. American Produc-tivity and Quality Council.
 [Swartz, M. F. and Wood, D. C. M. 1993. Discovering shared interests using graph analysis. Communications of the ACM. 36(8): 78-89.
 Lamont, J. June 2006. Finding Experts: Explicit and Implicit. KM World 15(6): 10-11, 24.