September 08 to 10 2014, Santa Clara, USA.


Speaker "Amit Nithianandan" Details

Name :
amit nithianandan
Company :
Title :
Software Engineer
Topic :

Building Next Generation, Personalized Search Applications

Abstract :

Search engines help people wade through mountains of information quickly and efficiently. Apache’s Solr is one of the most popular open source search engines, enabling people to build large scale search applications customized for their domains. For example, e-commerce companies rely on search technology allows users to find exactly what they want to buy. As search becomes more pervasive, the next generation of search applications will require results returned that are not only relevant to the query terms specified, but also based on external factors such as geolocation, personal preference, past purchase history, viewing history, etc. Therefore, it becomes increasingly important that applications move to smaller form factors, such as mobile and wearable devices (i.e. Google Glass). In these situations, the penalty for a bad result is significantly higher, justifying the need for systems capable of delivering highly-relevant, personalized results. Hadoop and HBase allow developers to store and process large amounts of information than can be used to aid in decision making and Solr has also been used to power user facing search applications. However, tying these pieces of infrastructure together isn’t trivial, especially if your goal is to offer each user a customized search experience. In this presentation we'll discuss how developers can leverage the power Kiji, Wibidata’s open source framework built on top of Hadoop and HBase, to store and process user specific data both in batch and real-time. We’ll demonstrate (with a live prototype application using the MovieLens dataset) the use of machine learning techniques within the Kiji framework to help augment user queries with preference information and finally demonstrate how this information can be combined with Apache’s Solr to produce relevant, personalized search results.

Profile :
Amit Nithianandan is a Member of the Technical Staff on the platform engineering team at WibiData and is a contributor to the Kiji Project. Prior to WibiData, Amit was the lead search and analytics engineer at (now a part of eBay) where he worked on search infrastructure, relevance and the integration of access log analytics into the search engine.

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