International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 28 | Number 1 | Year 2015 | Article Id. IJCTT-V28P132 | DOI : https://doi.org/10.14445/22312803/IJCTT-V28P132

An Agent Based Catalog Integration System through Active Learning

G.Sindhu Priya, P.Krubhala, P.Niranjana

Citation :

G.Sindhu Priya, P.Krubhala, P.Niranjana, "An Agent Based Catalog Integration System through Active Learning," International Journal of Computer Trends and Technology (IJCTT), vol. 28, no. 1, pp. 172-175, 2015. Crossref, https://doi.org/10.14445/22312803/IJCTT-V28P132

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.

Keywords

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

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