Abstract——In many applications that require decision making, dependency is on the data obtained from various sources. Each source of information provides a different perspective to the problem domain. With the existing data that is available and new perspective that evolves at later stages, there is need to learn incrementally. In this paper we recognize the similarity between the new perspective and the existing knowledge based on their pattern. The proposed work, referred as ‘Multi-Perspective based Incremental Learning’ [MPIL], effectively modifies the knowledge with available perspectives, understands the patterns of the data to determine the update and at the same time maintains them for reuse. With application to education sector, experiments show that the proposed approach exhibit better decision-making capacity in a multi-perspective environment.
Index Terms—Clustering, decision-making, incremental, pattern recognition.
P. Joshi is Research Scholar at College of Engineering Pune and is working with MIT College of Engineering, Pune (e-mail: prachi.joshi@mit.edu.in).
P. Kulkarni was Chief Scientist with Capsilon India Pvt. Ltd. and currently is the Chief Scientist and founder of Eklat Research, Pune (e-mail: paragakulkarni@yahoo.com).
Cite: Prachi Joshi and Parag Kulkarni, "Decision-Making in Multi-Perspective Environment with Incremental Learning," International Journal of Modeling and Optimization vol. 2, no. 2, pp. 109-113 , 2012.
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