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Friday, October 14 • 11:20am - 12:00pm
Challenges of e-commerce product search and the case study of the Home Depot enterprise search
In this talk, three independent but connected topics are discussed. On top of the baseline Solr and Fusion engine, how the Home Depot extends Solr to solve their unique business rule requirements, implement intelligent type-ahead system, and tune search relevancy in a scientific way instead of using black magic. Along with many other unique solutions, The Home Depot established their enterprise search engine using Solr.

The Home Depot used to be one of the biggest Endeca customers. While developing extensions to the Endeca system, this proprietary system become more and more a barrier to the ever increasing business demands. Solr and Fusion offered flexibility and a certain amount of out-of-box functionalities, but the Home Depot search and personalization team still needed to extend the platform to come up with a comprehensive solution to meet their technical requirements. This talk provides a case study in hoping the audiences can benefit from the material to expand their search engine to the next level.

Speakers
avatar for Senthil Murugan

Senthil Murugan

Principal Consultant, Mindtree Ltd.
Senthil Murugan received B.Tech degree from Anna University, India in 2005 and currently designated as Principal Consultant at Mindtree Ltd. Senthil is currently working with HomeDepot's Search and Personalization team as a Contractor for Enterprise Search Implementation project. Senthil's interest are around building B2B/B2C ecommerce applications, micro services development and Endeca/SOLR search engine integration.
avatar for Rongkai (Alfred) Zhao

Rongkai (Alfred) Zhao

IT Architect, The Home Depot
Rongkai (Alfred) Zhao received Ph.D in computer science from University of Illinois at Urbana-Champaign in 2005 and currently is an architect for The Home Depot. Rongkai works in the search and personalization team, his responsibility is to provide architectural solution and lead data science effort in the team. Rongkai’s research interest is information retrieval, deep learning, natural language processing and computer vision.


Friday October 14, 2016 11:20am - 12:00pm
Back Bay A Sheraton Boston