UCTV Seminars

description:

Discussion of the big data problem of recommending good matches from large databases. In my personal research in the area of music recommendation, solving this problem allows to provide relevant or similar song recommendations, given a user query consisting of one or more seed songs (e.g., playlist generation for online radio). This big data problem is also core and center to an effort I recently started, to provide academic researchers with access to alternative funding sources, by using data-driven algorithms to match researchers with philanthropists and create long-term engagements.

more on this subject:

Tracing Narratives - Understanding Patterns of Tension and Surprise in Music, Myth and Film

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host links:

UCSD Office of Research Affairs Web Site

more from this conference:

Opening Remarks - Sandy Brown and Phil Bourne - Big Data at UCSD

Using Twitter Data to Predict Flu Outbreak

Real-Time Streaming Data from Electricity Grids: Distributed Event Detection and Dynamic Modeling

End-to-end Data Solutions for Simulations at Extreme-scale

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