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Socializing Search. Professionally.

Sriram Sankar (LinkedIn), Daniel Tunkelang (Various)
Data in Action
Ballroom CD
Average rating: ****.
(4.75, 4 ratings)

LinkedIn has a unique data collection: the 238M+ members who use LinkedIn are also the most valuable entities in our corpus, which consists of people, companies, jobs, and a rich content ecosystem. Our members use LinkedIn to satisfy a diverse set of navigational and exploratory information needs, which we address by leveraging semi-structured and social content to understanding their query intent and deliver a personalized search experience.

As a result, we’ve built a system quite different from those used for web or enterprise search. In this talk, we will discuss how we have addressed the unique scalability, performance, and search quality challenges in order to deliver billions of deeply personalized searches to our members. Although many of the challenges we face are unique to LinkedIn, we hope that the ideas we share will prove useful to other folks thinking about entity-oriented search or working with large-scale social network data.

Sriram Sankar

Principal Staff Engineer, LinkedIn

Sriram Sankar is a Principal Staff Engineer at LinkedIn, where he is leading the development of our next-generation search infrastructure. Before that, he led Facebook’s search quality and ranking efforts for Graph Search. He previously worked at Google on search quality and ads infrastructure and held senior technical roles at VMware, WebGain, and Sun. He was a key contributor to Unicorn, the index powering Facebook’s Graph Search, and developed JavaCC, the leading parser generator for Java. He is a graduate of the Indian Institute of Technology in Kanpur.

Photo of Daniel Tunkelang

Daniel Tunkelang

Advisor, Various

Daniel Tunkelang leads LinkedIn’s efforts around query understanding. Before that, he led LinkedIn’s product data science team. He previously led a local search quality team at Google and was a founding employee of Endeca (acquired by Oracle in 2011). He has written a textbook on faceted search, and is a recognized advocate of human-computer interaction and information retrieval (HCIR). He has spoken at three previous Strata conferences, and is on the editorial board of the Journal of Big Data. He has a PhD in Computer Science from CMU, as well as BS and MS degrees from MIT.