Vidhya Ramachandran is a Director of Engineering at Priceline (a Booking Holdings online travel company) in the Platform Services team. In her current role, she has architected highly scalable, low-latency, distributed Big data and Information Retrieval systems employing Machine Learned ranking. She is passionate about Distributed Systems, Information Retrieval, and personalization in particular. She relishes working on complex technical problems that have a deep impact on the business. She also enjoys mentoring and motivating teams. She recently won a company-wide Hackathon presenting a Personalized Recommendation solution. When she is not working, she turns her passion for technology to do fun projects with her 13-year-old son.
Srividhya Ramachandran is speaking at the following session/s
Suggest, Search and Recommendations in Priceline based on Solr
Come listen to how Priceline uses Solr Cloud for serving Auto-suggest, Search and Recommendations to Customers in low latency services. They will talk about their story on recent migration from Lucene based services to Solr Cloud-based Indexing Services for Auto Suggest and fine-tuned their queries. Their feedback mechanisms on ranking documents based on user selections, calculation of relevancy score and use of LTR to re-rank based on other signals in data have been fine-tuned to meet their business needs. Recently they also built a personalized recommendation system on Solr, using Streaming and Graph Traversal.
Experimentation and continuous improvement on Auto Suggest and Search components that increased customer engagement will be discussed along with new use cases like the personalized recommendations systems.
Teams looking to migrate to Solr Cloud and getting their feet wet with custom ranking and re-ranking are perfect candidates to attend this session.