An Agent Based Catalog Integration System through Active Learning
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-28 Number-4 |
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| Year of Publication : 2015 | ||
| Authors : G.Sindhu Priya, P.Krubhala, P.Niranjana | ||
| DOI : 10.14445/22312803/IJCTT-V28P132 |
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.