An Agent Based Catalog Integration System through Active Learning

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-28 Number-4
Year of Publication : 2015
Authors : G.Sindhu Priya, P.Krubhala, P.Niranjana
  10.14445/22312803/IJCTT-V28P132

MLA

G.Sindhu Priya, P.Krubhala, P.Niranjana "An Agent Based Catalog Integration System through Active Learning". International Journal of Computer Trends and Technology (IJCTT) V28(4):172-175, October 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Online Commercial data integration plays a vital role in categorizing the products from multiple providers all over the globe. An unique taxonomy is maintained by the Commercial portals and products of the providers are associated with their own taxonomy. In the existing work, an efficient and scalable approach to Catalog Integration is used which is based on the use of Source Category and Taxonomy structure Information. We formulate this intuition as a structured prediction optimization problem. Learning algorithms can actively query the user for labels. Active learning concept is used to identify candidate products for labeling and also used to obtain the desired outputs at new data points. It intends to develop the catalog integration process in automated fashion in an agent based environment in which agent can cooperate interact with the consumers to find the best classification based upon the consumer preferences.

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Keywords
Active learning, Catalog Integration, classification, Master taxonomy, Provider taxonomy, Agent.