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Expertization Level Ranking for Query Transformation

Affiliations

  • Department of Computer Applications, B. S. Abdur Rahman University, Chennai - 600048, Tamil Nadu, India

Abstract


Objectives: To develop an approach to find one’s expertization level in a given field. Methods/Statistical Analysis: The search engines were utilized to extract the expert’s data available in the internet. The results generated by the search engines were downloaded in the database. Intern these results were used as an input to the relevance and expertise mapping process. We have used Relevance Algorithm and Expertise Mapping Algorithm to process the data generated by the search engines. These process yields one’s expertization level on a particular area. Findings: E-learning systems were automated to identify an expert by using two methods self-classification and document-based-relevance. These methods assume that relevance of one’s specified keywords or documents to the query is positively related to their expertise. In reality, one can be identified as an expert in a specific domain by the contribution made on that particular domain. The expert expertization data available in websites could be utilized by the e-learning systems to evaluate the expert’s. Hence it is proposed to ensure the expertise level of an expert using a Dynamic Expertization Estimating System (DEES) in an e-learning environment. In this approach, search engines were utilized as an agent to extract the expert’s data available in the internet and weightage were given to the expert according to their contribution made by the expert towards the given expertise area. The results retrieved by applying this mechanism yielded data with high accuracy levels to ensure the expertization level of an expert. Application/Improvements: Connecting the Dynamic Expertization Estimating System (DEES) with social media to fetch more data pertaining to the expert expertization and produce accurate expertise level for each expert.

Keywords

E-learning System, Expert Finding, Knowledge Management, Knowledge Sharing, Knowledge Capture, Tacit Knowledge.

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References


  • Wang G, Alan A. ExpertRank: A topic-aware expert finding algorithm for online knowledge communities. Decision Support Systems. 2013; 54(3):1442–51.
  • Moreira M, Catarina C, Martins B, Calado P. Using rank aggregation for expert search in academic digital libraries. Ar Xivpreprint. Portugal; 2015. p. 1–13.
  • Kardan K, Hendijanifard K. Expert finding system in e-learning. Using concept maps. International Journal of Information and Communication Technology. 2011; 3(1):73–81.
  • Macdonald C, Ounis I. Voting techniques for expert search. Knowledge and Information Systems. 2008; 16(3):259–80.
  • Serdyukov P. Search for Expertise: Going beyond direct evidence [PhD thesis]. University of Twente; 2009. p. 1–158.
  • Soboroff I, Vries APD, Craswell N. Overview of the TREC-2006 enterprise track. Proceedings of the 15th Text Retrieval Conference; UK. 2007. p. 1–20.
  • Craswell N, Vries APD, Soboroff I. Overview of the TREC-2005 enterprise track. Proceedings of the 14th Text Retrieval Conference; USA. 2006. p. 1–7.
  • Balog K, Azzopardi L, Rijke MD. Formal models for expert finding in enterprise corpora. Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; USA. 2006. p. 43–50.
  • Wang G, Alan A. ExpertRank: A topic-aware expert finding algorithm for online knowledge communities. Decision Support Systems. 2013; 54(3):1442–51.
  • Mirsaeedghazi T, Mahmood K, Ahmad K, Neda E. A framework for learner preparation and support in academic e-learning environment. International Journal of Information and Communication Technology. 2011; 3(1):33–41.
  • Liu L, Duen-Ren D. Integrating expert profile, reputation and link analysis for expert finding in question-answering websites. Information Processing and Management. 2013; 49(1):312–29.
  • Venkataramanan M, Prema TS, Nandini SV. Knowledge management through distance education. Indian Journal of Science and Technology. 2011 Mar; 4(3):1–3.
  • Nikabadi MS, Dehghan M, Farmanian-Arani M. The effect of knowledge management strategies on performance of new product development in knowledge-based companies. Indian Journal of Science and Technology. 2015 Apr; 8(S7):1–15.
  • Monisha S, Saranya R, Vijay K. Gauzy knowledge sharing in conspiring environment using text mining. Indian Journal of Science and Technology. 2016 Jul; 9(27):1–5.

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